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List of abstracts related to

82092 Accurate prediction of glaucoma from colour fundus images with a convolutional neural network that relies on active and transfer learning
Hemelings R; Elen B; Barbosa-Breda J; Lemmens S; Meire M; Pourjavan S; Vandewalle E; Van de Veire S; Blaschko MB; De Boever P; Stalmans I
Acta Ophthalmologica 2020; 98: e94-e100

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6.9.5 Other (925 abstracts found)


84734 Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior
Zhou W
Computational and mathematical methods in medicine 2019; 2019: 8973287 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Jammal AA
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


84090 Glaucoma Detection from Retinal Images Using Statistical and Textural Wavelet Features
Abdel-Hamid L
Journal of digital imaging 2020; 33: 151-158 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Lee K
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Li F
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85101 Diagnosis of Glaucoma on Retinal Fundus Images Using Deep Learning: Detection of Nerve Fiber Layer Defect and Optic Disc Analysis
Muramatsu C
Adv Exp Med Biol 2020; 1213: 121-132 (IGR: 21-1)


84652 Automatic Anterior Chamber Angle Measurement for Ultrasound Biomicroscopy Using Deep Learning
Li W
Journal of Glaucoma 2020; 29: 81-85 (IGR: 21-1)


84506 Regional Patterns in Retinal Microvascular Network Geometry in Health and Disease
Popovic N
Scientific reports 2019; 9: 16340 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Zapata MA
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Ha A
Scientific reports 2019; 9: 19771 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Bambo MP
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


84979 Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and Meta-analysis
Murtagh P
International Journal of Ophthalmology 2020; 13: 149-162 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Fuentemilla E
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Royo-Fibla D
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Thompson AC
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


84734 Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior
Yi Y
Computational and mathematical methods in medicine 2019; 2019: 8973287 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Sun S
Scientific reports 2019; 9: 19771 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Yan L
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


84979 Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and Meta-analysis
Greene G
International Journal of Ophthalmology 2020; 13: 149-162 (IGR: 21-1)


84652 Automatic Anterior Chamber Angle Measurement for Ultrasound Biomicroscopy Using Deep Learning
Chen Q
Journal of Glaucoma 2020; 29: 81-85 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Bae HW
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


84506 Regional Patterns in Retinal Microvascular Network Geometry in Health and Disease
Vujosevic S
Scientific reports 2019; 9: 16340 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Kim YK
Scientific reports 2019; 9: 19771 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Lee SY
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


84979 Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and Meta-analysis
O'Brien C
International Journal of Ophthalmology 2020; 13: 149-162 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Mariottoni EB
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


84652 Automatic Anterior Chamber Angle Measurement for Ultrasound Biomicroscopy Using Deep Learning
Jiang Z
Journal of Glaucoma 2020; 29: 81-85 (IGR: 21-1)


84734 Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior
Gao Y
Computational and mathematical methods in medicine 2019; 2019: 8973287 (IGR: 21-1)


84506 Regional Patterns in Retinal Microvascular Network Geometry in Health and Disease
Popovic T
Scientific reports 2019; 9: 16340 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Mariottoni EB
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Cameo B
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Font O
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Wang Y
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Jeoung JW
Scientific reports 2019; 9: 19771 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Berchuck SI
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Vela JI
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Berchuck SI
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Fuertes I
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


84652 Automatic Anterior Chamber Angle Measurement for Ultrasound Biomicroscopy Using Deep Learning
Deng G
Journal of Glaucoma 2020; 29: 81-85 (IGR: 21-1)


84734 Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior
Dai J
Computational and mathematical methods in medicine 2019; 2019: 8973287 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Shi J
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Seong GJ
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Chen H
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Ferrandez B
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Kim HC
Scientific reports 2019; 9: 19771 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Kim CY
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Marcantonio I
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Urata CN
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


84652 Automatic Anterior Chamber Angle Measurement for Ultrasound Biomicroscopy Using Deep Learning
Zong Y
Journal of Glaucoma 2020; 29: 81-85 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Estrela T
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


84652 Automatic Anterior Chamber Angle Measurement for Ultrasound Biomicroscopy Using Deep Learning
Shi G
Journal of Glaucoma 2020; 29: 81-85 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Zhang X
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Güerri N
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Moya-Sánchez EU
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Estrela T
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Park KH
Scientific reports 2019; 9: 19771 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Sánchez-Pérez A
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Jiang M
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


84652 Automatic Anterior Chamber Angle Measurement for Ultrasound Biomicroscopy Using Deep Learning
Jiang C
Journal of Glaucoma 2020; 29: 81-85 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Polo V
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Wakil SM
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


84652 Automatic Anterior Chamber Angle Measurement for Ultrasound Biomicroscopy Using Deep Learning
Sun X
Journal of Glaucoma 2020; 29: 81-85 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Wu Z
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Garcia-Gasulla D
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Larrosa JM
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Costa VP; Medeiros FA
American Journal of Ophthalmology 2020; 211: 123-131 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Pablo LE
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Zhou K
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Cortés U; Ayguadé E
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85052 Diagnostic capability of a linear discriminant function applied to a novel Spectralis OCT glaucoma-detection protocol
Garcia-Martin E
BMC Ophthalmology 2020; 20: 35 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Labarta J
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


82612 Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples
Xu YL
Sensors (Basel, Switzerland) 2019; 19: (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Rogers TW
Eye 2019; 33: 1791-1797 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Mao Z
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82333 Automated anterior chamber angle pigmentation analyses using 360° gonioscopy
Matsuo M
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Hao H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Shang Q
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


82109 Variance components for PIMD-2π estimation of the optic nerve head and consequences in clinical measurements of glaucoma
Sandberg Melin C
Acta Ophthalmologica 2020; 98: 190-194 (IGR: 20-4)


82875 Glaucoma Assessment from OCT images using Capsule Network
Gaddipati DJ
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 5581-5584 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Liu H
JAMA ophthalmology 2019; 0: (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Pujari A
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82872 A New Texture-Based Segmentation Method for Optical Coherence Tomography Images
Monemian M
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4750-4753 (IGR: 20-4)


82796 Multi-indices quantification of optic nerve head in fundus image via multitask collaborative learning
Zhao R
Medical Image Analysis 2020; 60: 101593 (IGR: 20-4)


82744 Glaucoma detection using image processing techniques: A literature review
Sarhan A
Computerized Medical Imaging and Graphics 2019; 78: 101657 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Orlando JI
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Fu H
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82867 A novel method for retinal vessel segmentation and diameter measurement using high speed video
Rezaeian M
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2781-2784 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Hao H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Liu S
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Snyder BM
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Bajwa MN
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Wang J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Zhao R
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82450 The impact of artificial intelligence in the diagnosis and management of glaucoma
Mayro EL
Eye 2020; 34: 1-11 (IGR: 20-4)


82776 Automated detection of glaucoma using optical coherence tomography angiogram images
Chan YM
Computers in Biology and Medicine 2019; 115: 103483 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Phene S
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Devalla SK
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82206 Ophthalmic Research Lecture 2018: DARC as a Potential Surrogate Marker
Yap TE
Ophthalmic Research 2020; 63: 1-7 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Raghavendra U
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Liao W
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Chiquet C
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82453 Fully automated method for glaucoma screening using robust optic nerve head detection and unsupervised segmentation based cup-to-disc ratio computation in retinal fundus images
Mvoulana A
Computerized Medical Imaging and Graphics 2019; 77: 101643 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Thakoor KA
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82099 Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis
Zhou W
Medical and Biological Engineering and Computing 2019; 57: 2055-2067 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Amil P
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82733 Using soft computing techniques to diagnose Glaucoma disease
Al-Akhras M
Journal of infection and public health 2019; 0: (IGR: 20-4)


81601 Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation
Wang S
IEEE Transactions on Medical Imaging 2019; 38: 2485-2495 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Phasuk S
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Shang Q
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Christopher M
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Malik MI
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82453 Fully automated method for glaucoma screening using robust optic nerve head detection and unsupervised segmentation based cup-to-disc ratio computation in retinal fundus images
Kachouri R
Computerized Medical Imaging and Graphics 2019; 77: 101643 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Reyes-Manzano CF
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Dunn RC
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Hong J
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Selvan H
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Zhao Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Tantibundhit C
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Chen X
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Fu H
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Gudigar A
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82450 The impact of artificial intelligence in the diagnosis and management of glaucoma
Wang M
Eye 2020; 34: 1-11 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Miki A
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


81601 Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation
Yu L
IEEE Transactions on Medical Imaging 2019; 38: 2485-2495 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Nam SM
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Bowd C
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Yan Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Li X
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82733 Using soft computing techniques to diagnose Glaucoma disease
Barakat A
Journal of infection and public health 2019; 0: (IGR: 20-4)


82867 A novel method for retinal vessel segmentation and diameter measurement using high speed video
Butlin M
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2781-2784 (IGR: 20-4)


82206 Ophthalmic Research Lecture 2018: DARC as a Potential Surrogate Marker
Shamsher E
Ophthalmic Research 2020; 63: 1-7 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Li L
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zou B
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Baskaran M
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Zhao Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Liang Z
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82099 Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis
Yi Y
Medical and Biological Engineering and Computing 2019; 57: 2055-2067 (IGR: 20-4)


82109 Variance components for PIMD-2π estimation of the optic nerve head and consequences in clinical measurements of glaucoma
Yu Z
Acta Ophthalmologica 2020; 98: 190-194 (IGR: 20-4)


82333 Automated anterior chamber angle pigmentation analyses using 360° gonioscopy
Pajaro S
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Gavard O
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82872 A New Texture-Based Segmentation Method for Optical Coherence Tomography Images
Rabbani H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4750-4753 (IGR: 20-4)


82796 Multi-indices quantification of optic nerve head in fundus image via multitask collaborative learning
Li S
Medical Image Analysis 2020; 60: 101593 (IGR: 20-4)


82744 Glaucoma detection using image processing techniques: A literature review
Rokne J
Computerized Medical Imaging and Graphics 2019; 78: 101657 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Jaccard N
Eye 2019; 33: 1791-1797 (IGR: 20-4)


82875 Glaucoma Assessment from OCT images using Capsule Network
Desai A
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 5581-5584 (IGR: 20-4)


82776 Automated detection of glaucoma using optical coherence tomography angiogram images
Ng EYK
Computers in Biology and Medicine 2019; 115: 103483 (IGR: 20-4)


82612 Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples
Lu S
Sensors (Basel, Switzerland) 2019; 19: (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Xiyao L
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Hammel N
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82109 Variance components for PIMD-2π estimation of the optic nerve head and consequences in clinical measurements of glaucoma
Söderberg PG
Acta Ophthalmologica 2020; 98: 190-194 (IGR: 20-4)


82744 Glaucoma detection using image processing techniques: A literature review
Alhajj R
Computerized Medical Imaging and Graphics 2019; 78: 101657 (IGR: 20-4)


82867 A novel method for retinal vessel segmentation and diameter measurement using high speed video
Golzan SM
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2781-2784 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Siddiqui SA
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Arnould L
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Tsamis E
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82206 Ophthalmic Research Lecture 2018: DARC as a Potential Surrogate Marker
Guo L
Ophthalmic Research 2020; 63: 1-7 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zhao R
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82453 Fully automated method for glaucoma screening using robust optic nerve head detection and unsupervised segmentation based cup-to-disc ratio computation in retinal fundus images
Akil M
Computerized Medical Imaging and Graphics 2019; 77: 101643 (IGR: 20-4)


82776 Automated detection of glaucoma using optical coherence tomography angiogram images
Jahmunah V
Computers in Biology and Medicine 2019; 115: 103483 (IGR: 20-4)


82099 Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis
Bao J
Medical and Biological Engineering and Computing 2019; 57: 2055-2067 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Pham TH
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


81601 Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation
Yang X
IEEE Transactions on Medical Imaging 2019; 38: 2485-2495 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Tsamis E
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Khunsongkiet P
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Belghith A
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Barbosa Breda J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82875 Glaucoma Assessment from OCT images using Capsule Network
Sivaswamy J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 5581-5584 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Mei S
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Guzmán-Vargas L
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Wormstone IM
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82733 Using soft computing techniques to diagnose Glaucoma disease
Alawairdhi M
Journal of infection and public health 2019; 0: (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Xu Y
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82612 Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples
Li HX
Sensors (Basel, Switzerland) 2019; 19: (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Poopresert P
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Carbonaro F
Eye 2019; 33: 1791-1797 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Xu Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Fu H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Lu X
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Asif MI
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82450 The impact of artificial intelligence in the diagnosis and management of glaucoma
Elze T
Eye 2020; 34: 1-11 (IGR: 20-4)


82333 Automated anterior chamber angle pigmentation analyses using 360° gonioscopy
De Giusti A
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Tsamis E
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Chen Z
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Bhandary SV
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Sajda P
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Mautuit T
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82099 Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis
Wang W
Medical and Biological Engineering and Computing 2019; 57: 2055-2067 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Goldbaum MH
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82875 Glaucoma Assessment from OCT images using Capsule Network
Vermeer KA
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 5581-5584 (IGR: 20-4)


82733 Using soft computing techniques to diagnose Glaucoma disease
Habib M
Journal of infection and public health 2019; 0: (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Boote C
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Dengel A
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Liu Y
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Ausayakhun S
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82612 Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples
Li RR
Sensors (Basel, Switzerland) 2019; 19: (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Qiao C
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82450 The impact of artificial intelligence in the diagnosis and management of glaucoma
Pasquale LR
Eye 2020; 34: 1-11 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Zhao W
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82333 Automated anterior chamber angle pigmentation analyses using 360° gonioscopy
Tanito M
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Hao H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


81601 Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation
Fu CW
IEEE Transactions on Medical Imaging 2019; 38: 2485-2495 (IGR: 20-4)


82867 A novel method for retinal vessel segmentation and diameter measurement using high speed video
Graham SL
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2781-2784 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Jia X
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Gupta B
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Shang Q
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Dong Y
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Zailiang C
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Sendiña-Nadal I
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82776 Automated detection of glaucoma using optical coherence tomography angiogram images
Wei Koh JE
Computers in Biology and Medicine 2019; 115: 103483 (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Hao H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Yaemsuk A
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Chen Y
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Van Keer K
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Rao TN
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Lin S
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Shang Q
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82206 Ophthalmic Research Lecture 2018: DARC as a Potential Surrogate Marker
Cordeiro MF
Ophthalmic Research 2020; 63: 1-7 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Lemij HG
Eye 2019; 33: 1791-1797 (IGR: 20-4)


81601 Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation
Heng PA
IEEE Transactions on Medical Imaging 2019; 38: 2485-2495 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Li F
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Leeungurasatien T
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82776 Automated detection of glaucoma using optical coherence tomography angiogram images
Lih OS
Computers in Biology and Medicine 2019; 115: 103483 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Krause J
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Vermeer KA
Eye 2019; 33: 1791-1797 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Guo F
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


81601 Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation
Heng PA
IEEE Transactions on Medical Imaging 2019; 38: 2485-2495 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Masoller C
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Macgillivray TJ
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Wong DWK
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Zhang C
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Lin Z
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Weinreb RN
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Suvannachart P
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Ciaccio EJ
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Shafait F
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
He Z
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Hood DC
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Li F
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


82867 A novel method for retinal vessel segmentation and diameter measurement using high speed video
Avolio AP
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2781-2784 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Strouthidis NG
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Maruyama K
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Min H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Bathula DR
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Dada T
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zhou M
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Diaz-Pinto A
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Zhou Y
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Thiery AH
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Tan M
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Liu J
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Zhang X
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Itthipanichpong R
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Acharya UR
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Fazio MA
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Diaz-Pinto A
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Zhang X
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Bron AM
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Kitade N
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82776 Automated detection of glaucoma using optical coherence tomography angiogram images
Wei Leon LY
Computers in Biology and Medicine 2019; 115: 103483 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Reus NJ
Eye 2019; 33: 1791-1797 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Liu P
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Leiter MR
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Neumeier W
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Li S
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Kawasaki R
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Liu J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Schaekermann M
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82776 Automated detection of glaucoma using optical coherence tomography angiogram images
Acharya UR
Computers in Biology and Medicine 2019; 115: 103483 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Liu Y
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Usui S
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82871 Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Liu J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Trikha S
Eye 2019; 33: 1791-1797 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Chansangpetch S
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Fang R
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Semecas R
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Liu J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Li S
JAMA ophthalmology 2019; 0: (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Tun TA
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Sevastopolsky A
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Ahmed S
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Girkin CA
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Girard MJA
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Heng PA
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Wang H
JAMA ophthalmology 2019; 0: (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Mahesh M
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Heng PA
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Sayres R
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Manassakorn A
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Trucco E
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Matsushita K
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Liebmann JM
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Zhang H
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Joye AS
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Perera SA
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Berlinberg EJ
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Kim J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Nishida K
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Wu DJ
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Mou D
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Zangwill LM
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Tantisevi V
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Florent A
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Chan K
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Rojanapongpun P
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Bora A
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


81618 A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
Aung T
American Journal of Ophthalmology 2019; 203: 37-45 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Liu Y
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Lee J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Pang R
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Ramirez DA
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Yang D
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Semturs C
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Jiang L
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Moe CA
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Li X
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Misra A; Huang AE
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Liu P
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Chen Y
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Spitze A
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Stamper RL
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Lu S
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Hu M
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Medeiros FA
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Murugesan B
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82193 Accuracy of computer-assisted vertical cup-to-disk ratio grading for glaucoma screening
Keenan JD
PLoS ONE 2019; 14: e0220362 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Xu Y; Kang H
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Naranjo V
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Maa AY
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Naranjo V; Phaye SSR
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Ji X
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Gandhi M
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Shankaranarayana SM
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Corrado GS
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Chang R
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Peng L
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Tham C
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Sikka A
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Webster DR
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Son J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Cheung C; Ting DSW
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
van den Hengel A; Wang S
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Wong TY; Wang Z
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Wu J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Weinreb RN
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Wu Z
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Xu M
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Xu G; Xu Y
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Wang N
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Yin
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


81146 Machine Learning in the Detection of the Glaucomatous Disc and Visual Field
Smits DJ
Seminars in Ophthalmology 2019; 34: 232-242 (IGR: 20-3)


80853 Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
Jang H
Korean Journal of Ophthalmology 2019; 33: 103-112 (IGR: 20-3)


80477 Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation
Shankaranarayana SM
IEEE journal of biomedical and health informatics 2019; 23: 1417-1426 (IGR: 20-3)


81053 Primary Acute Angle-Closure Glaucoma: Three-Dimensional Reconstruction Imaging of Optic Nerve Heard Structure in Based on Optical Coherence Tomography (OCT)
Wang Y
Medical Science Monitor 2019; 25: 3647-3654 (IGR: 20-3)


80518 Evaluation of deep convolutional neural networks for glaucoma detection
Phan S
Japanese Journal of Ophthalmology 2019; 63: 276-283 (IGR: 20-3)


81341 Clinical validation of , an automated optic nerve head analysis software
Singh D; Gunasekaran S
Indian Journal of Ophthalmology 2019; 67: 1089-1094 (IGR: 20-3)


80853 Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
Lee SM
Korean Journal of Ophthalmology 2019; 33: 103-112 (IGR: 20-3)


81053 Primary Acute Angle-Closure Glaucoma: Three-Dimensional Reconstruction Imaging of Optic Nerve Heard Structure in Based on Optical Coherence Tomography (OCT)
Chen D
Medical Science Monitor 2019; 25: 3647-3654 (IGR: 20-3)


81146 Machine Learning in the Detection of the Glaucomatous Disc and Visual Field
Elze T
Seminars in Ophthalmology 2019; 34: 232-242 (IGR: 20-3)


80518 Evaluation of deep convolutional neural networks for glaucoma detection
Satoh S
Japanese Journal of Ophthalmology 2019; 63: 276-283 (IGR: 20-3)


80477 Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation
Ram K; Mitra K
IEEE journal of biomedical and health informatics 2019; 23: 1417-1426 (IGR: 20-3)


80518 Evaluation of deep convolutional neural networks for glaucoma detection
Yoda Y
Japanese Journal of Ophthalmology 2019; 63: 276-283 (IGR: 20-3)


81053 Primary Acute Angle-Closure Glaucoma: Three-Dimensional Reconstruction Imaging of Optic Nerve Heard Structure in Based on Optical Coherence Tomography (OCT)
Yang W
Medical Science Monitor 2019; 25: 3647-3654 (IGR: 20-3)


81341 Clinical validation of , an automated optic nerve head analysis software
Hada M
Indian Journal of Ophthalmology 2019; 67: 1089-1094 (IGR: 20-3)


80853 Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
Ahn J
Korean Journal of Ophthalmology 2019; 33: 103-112 (IGR: 20-3)


81146 Machine Learning in the Detection of the Glaucomatous Disc and Visual Field
Wang H; Pasquale LR
Seminars in Ophthalmology 2019; 34: 232-242 (IGR: 20-3)


80518 Evaluation of deep convolutional neural networks for glaucoma detection
Kashiwagi K
Japanese Journal of Ophthalmology 2019; 63: 276-283 (IGR: 20-3)


80477 Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation
Sivaprakasam M
IEEE journal of biomedical and health informatics 2019; 23: 1417-1426 (IGR: 20-3)


81341 Clinical validation of , an automated optic nerve head analysis software
Gogia V
Indian Journal of Ophthalmology 2019; 67: 1089-1094 (IGR: 20-3)


81053 Primary Acute Angle-Closure Glaucoma: Three-Dimensional Reconstruction Imaging of Optic Nerve Heard Structure in Based on Optical Coherence Tomography (OCT)
Cui Q
Medical Science Monitor 2019; 25: 3647-3654 (IGR: 20-3)


80853 Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
Rho S
Korean Journal of Ophthalmology 2019; 33: 103-112 (IGR: 20-3)


80518 Evaluation of deep convolutional neural networks for glaucoma detection
Oshika T
Japanese Journal of Ophthalmology 2019; 63: 276-283 (IGR: 20-3)


81053 Primary Acute Angle-Closure Glaucoma: Three-Dimensional Reconstruction Imaging of Optic Nerve Heard Structure in Based on Optical Coherence Tomography (OCT)
Hou W
Medical Science Monitor 2019; 25: 3647-3654 (IGR: 20-3)


80518 Evaluation of deep convolutional neural networks for glaucoma detection

Japanese Journal of Ophthalmology 2019; 63: 276-283 (IGR: 20-3)


81053 Primary Acute Angle-Closure Glaucoma: Three-Dimensional Reconstruction Imaging of Optic Nerve Heard Structure in Based on Optical Coherence Tomography (OCT)
Han W; Huang X; Lu W; Yuan Z; Yuan J; Teng Y; Qiu J
Medical Science Monitor 2019; 25: 3647-3654 (IGR: 20-3)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
MacCormick IJC
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79704 Artificial intelligence in glaucoma
Zheng C
Current Opinions in Ophthalmology 2019; 30: 97-103 (IGR: 20-2)


79863 A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs
Thompson AC
American Journal of Ophthalmology 2019; 201: 9-18 (IGR: 20-2)


79350 A deep learning model for the detection of both advanced and early glaucoma using fundus photography
Ahn JM
PLoS ONE 2018; 13: e0207982 (IGR: 20-2)


79439 A Unified Optic Nerve Head and Optic Cup Segmentation Using Unsupervised Neural Networks for Glaucoma Screening
Ghassabi Z
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 5942-5945 (IGR: 20-2)


79441 Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection
Jiang Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 862-865 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Shigueoka LS
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Christopher M
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79598 From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs
Medeiros FA
Ophthalmology 2019; 126: 513-521 (IGR: 20-2)


79559 Automated glaucoma diagnosis using bit-plane slicing and local binary pattern techniques
Maheshwari S
Computers in Biology and Medicine 2019; 105: 72-80 (IGR: 20-2)


79681 Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma
Keel S
JAMA ophthalmology 2019; 137: 288-292 (IGR: 20-2)


79598 From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs
Jammal AA
Ophthalmology 2019; 126: 513-521 (IGR: 20-2)


79439 A Unified Optic Nerve Head and Optic Cup Segmentation Using Unsupervised Neural Networks for Glaucoma Screening
Shanbehzadeh J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 5942-5945 (IGR: 20-2)


79350 A deep learning model for the detection of both advanced and early glaucoma using fundus photography
Kim S
PLoS ONE 2018; 13: e0207982 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Vasconcellos JPC
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79681 Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma
Wu J
JAMA ophthalmology 2019; 137: 288-292 (IGR: 20-2)


79704 Artificial intelligence in glaucoma
Johnson TV
Current Opinions in Ophthalmology 2019; 30: 97-103 (IGR: 20-2)


79441 Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection
Xia H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 862-865 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Williams BM
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Belghith A
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79863 A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs
Jammal AA
American Journal of Ophthalmology 2019; 201: 9-18 (IGR: 20-2)


79559 Automated glaucoma diagnosis using bit-plane slicing and local binary pattern techniques
Kanhangad V
Computers in Biology and Medicine 2019; 105: 72-80 (IGR: 20-2)


79681 Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma
Lee PY
JAMA ophthalmology 2019; 137: 288-292 (IGR: 20-2)


79441 Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection
Xu Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 862-865 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Zheng Y
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79598 From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs
Thompson AC
Ophthalmology 2019; 126: 513-521 (IGR: 20-2)


79704 Artificial intelligence in glaucoma
Garg A
Current Opinions in Ophthalmology 2019; 30: 97-103 (IGR: 20-2)


79863 A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs
Medeiros FA
American Journal of Ophthalmology 2019; 201: 9-18 (IGR: 20-2)


79559 Automated glaucoma diagnosis using bit-plane slicing and local binary pattern techniques
Pachori RB
Computers in Biology and Medicine 2019; 105: 72-80 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Bowd C
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79439 A Unified Optic Nerve Head and Optic Cup Segmentation Using Unsupervised Neural Networks for Glaucoma Screening
Nouri-Mahdavi K
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 5942-5945 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Schimiti RB
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79350 A deep learning model for the detection of both advanced and early glaucoma using fundus photography
Ahn KS
PLoS ONE 2018; 13: e0207982 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Reis ASC
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79559 Automated glaucoma diagnosis using bit-plane slicing and local binary pattern techniques
Bhandary SV
Computers in Biology and Medicine 2019; 105: 72-80 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Proudfoot JA
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79681 Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma
Scheetz J
JAMA ophthalmology 2019; 137: 288-292 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Li K
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79350 A deep learning model for the detection of both advanced and early glaucoma using fundus photography
Cho SH
PLoS ONE 2018; 13: e0207982 (IGR: 20-2)


79704 Artificial intelligence in glaucoma
Boland MV
Current Opinions in Ophthalmology 2019; 30: 97-103 (IGR: 20-2)


79441 Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection
Cheng J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 862-865 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Oliveira GO
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79559 Automated glaucoma diagnosis using bit-plane slicing and local binary pattern techniques
Acharya UR
Computers in Biology and Medicine 2019; 105: 72-80 (IGR: 20-2)


79441 Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection
Fu H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 862-865 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Goldbaum MH
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79350 A deep learning model for the detection of both advanced and early glaucoma using fundus photography
Lee KB
PLoS ONE 2018; 13: e0207982 (IGR: 20-2)


79681 Visualizing Deep Learning Models for the Detection of Referable Diabetic Retinopathy and Glaucoma
He M
JAMA ophthalmology 2019; 137: 288-292 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Al-Bander B
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79350 A deep learning model for the detection of both advanced and early glaucoma using fundus photography
Kim US
PLoS ONE 2018; 13: e0207982 (IGR: 20-2)


79441 Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection
Duan L
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 862-865 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Czanner S
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Weinreb RN
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Gomi ES
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Cheeseman R
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Girkin CA
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Vianna JAR
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79441 Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection
Meng Z
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 862-865 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Willoughby CE
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Liebmann JM
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Lisboa RDDR
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79441 Optic Disc and Cup Segmentation with Blood Vessel Removal from Fundus Images for Glaucoma Detection
Liu J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2018; 2018: 862-865 (IGR: 20-2)


79468 Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Zangwill LM
Scientific reports 2018; 8: 16685 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Medeiros FA
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Brown EN; Spaeth GL
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Costa VP
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


80020 Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile
Czanner G
PLoS ONE 2019; 14: e0209409 (IGR: 20-2)


79157 Artificial intelligence and deep learning in ophthalmology
Ting DSW
British Journal of Ophthalmology 2019; 103: 167-175 (IGR: 20-1)


79160 Automated gonioscopy photography for iridocorneal angle grading
Teixeira F
European Journal of Ophthalmology 2018; 0: 1120672118806436 (IGR: 20-1)


78765 Deep convolutional neural network-based patch classification for retinal nerve fiber layer defect detection in early glaucoma
Panda R
Journal of medical imaging (Bellingham, Wash.) 2018; 5: 044003 (IGR: 20-1)


79160 Automated gonioscopy photography for iridocorneal angle grading
Teixeira F
European Journal of Ophthalmology 2018; 0: 1120672118806436 (IGR: 20-1)


78779 Automated Detection of Retinal Nerve Fiber Layer by Texture-Based Analysis for Glaucoma Evaluation
Septiarini A
Healthcare informatics research 2018; 24: 335-345 (IGR: 20-1)


78844 An efficient optic cup segmentation method decreasing the influences of blood vessels
Yang C
Biomedical engineering online 2018; 17: 130 (IGR: 20-1)


78813 Fundus image classification methods for the detection of glaucoma: A review
Saba T
Microscopy Research and Technique 2018; 81: 1105-1121 (IGR: 20-1)


78332 The region of interest localization for glaucoma analysis from retinal fundus image using deep learning
Mitra A
Computer Methods and Programs in Biomedicine 2018; 165: 25-35 (IGR: 20-1)


79256 A Fully Automated 3D In-vivo Delineation and Shape Parameterization of the Human Lamina Cribrosa in Optical Coherence Tomography
Syga P
IEEE Transactions on Bio-Medical Engineering 2019; 66: 1422-1428 (IGR: 20-1)


78813 Fundus image classification methods for the detection of glaucoma: A review
Bokhari STF
Microscopy Research and Technique 2018; 81: 1105-1121 (IGR: 20-1)


79160 Automated gonioscopy photography for iridocorneal angle grading
Sousa DC
European Journal of Ophthalmology 2018; 0: 1120672118806436 (IGR: 20-1)


79256 A Fully Automated 3D In-vivo Delineation and Shape Parameterization of the Human Lamina Cribrosa in Optical Coherence Tomography
Sieluzycki C
IEEE Transactions on Bio-Medical Engineering 2019; 66: 1422-1428 (IGR: 20-1)


79157 Artificial intelligence and deep learning in ophthalmology
Pasquale LR
British Journal of Ophthalmology 2019; 103: 167-175 (IGR: 20-1)


78332 The region of interest localization for glaucoma analysis from retinal fundus image using deep learning
Banerjee PS
Computer Methods and Programs in Biomedicine 2018; 165: 25-35 (IGR: 20-1)


78765 Deep convolutional neural network-based patch classification for retinal nerve fiber layer defect detection in early glaucoma
Puhan NB
Journal of medical imaging (Bellingham, Wash.) 2018; 5: 044003 (IGR: 20-1)


78844 An efficient optic cup segmentation method decreasing the influences of blood vessels
Lu M
Biomedical engineering online 2018; 17: 130 (IGR: 20-1)


78779 Automated Detection of Retinal Nerve Fiber Layer by Texture-Based Analysis for Glaucoma Evaluation
Harjoko A
Healthcare informatics research 2018; 24: 335-345 (IGR: 20-1)


78844 An efficient optic cup segmentation method decreasing the influences of blood vessels
Duan Y
Biomedical engineering online 2018; 17: 130 (IGR: 20-1)


78813 Fundus image classification methods for the detection of glaucoma: A review
Sharif M
Microscopy Research and Technique 2018; 81: 1105-1121 (IGR: 20-1)


79160 Automated gonioscopy photography for iridocorneal angle grading
Leal I
European Journal of Ophthalmology 2018; 0: 1120672118806436 (IGR: 20-1)


78779 Automated Detection of Retinal Nerve Fiber Layer by Texture-Based Analysis for Glaucoma Evaluation
Pulungan R
Healthcare informatics research 2018; 24: 335-345 (IGR: 20-1)


79256 A Fully Automated 3D In-vivo Delineation and Shape Parameterization of the Human Lamina Cribrosa in Optical Coherence Tomography
Krzyzanowska-Berkowska P
IEEE Transactions on Bio-Medical Engineering 2019; 66: 1422-1428 (IGR: 20-1)


79157 Artificial intelligence and deep learning in ophthalmology
Peng L
British Journal of Ophthalmology 2019; 103: 167-175 (IGR: 20-1)


78765 Deep convolutional neural network-based patch classification for retinal nerve fiber layer defect detection in early glaucoma
Rao A
Journal of medical imaging (Bellingham, Wash.) 2018; 5: 044003 (IGR: 20-1)


78813 Fundus image classification methods for the detection of glaucoma: A review
Yasmin M
Microscopy Research and Technique 2018; 81: 1105-1121 (IGR: 20-1)


78332 The region of interest localization for glaucoma analysis from retinal fundus image using deep learning
Roy S
Computer Methods and Programs in Biomedicine 2018; 165: 25-35 (IGR: 20-1)


78779 Automated Detection of Retinal Nerve Fiber Layer by Texture-Based Analysis for Glaucoma Evaluation
Ekantini R
Healthcare informatics research 2018; 24: 335-345 (IGR: 20-1)


79256 A Fully Automated 3D In-vivo Delineation and Shape Parameterization of the Human Lamina Cribrosa in Optical Coherence Tomography
Iskander DR
IEEE Transactions on Bio-Medical Engineering 2019; 66: 1422-1428 (IGR: 20-1)


78765 Deep convolutional neural network-based patch classification for retinal nerve fiber layer defect detection in early glaucoma
Mandal B
Journal of medical imaging (Bellingham, Wash.) 2018; 5: 044003 (IGR: 20-1)


79157 Artificial intelligence and deep learning in ophthalmology
Campbell JP
British Journal of Ophthalmology 2019; 103: 167-175 (IGR: 20-1)


78844 An efficient optic cup segmentation method decreasing the influences of blood vessels
Liu B
Biomedical engineering online 2018; 17: 130 (IGR: 20-1)


79160 Automated gonioscopy photography for iridocorneal angle grading
Barata A
European Journal of Ophthalmology 2018; 0: 1120672118806436 (IGR: 20-1)


79157 Artificial intelligence and deep learning in ophthalmology
Lee AY
British Journal of Ophthalmology 2019; 103: 167-175 (IGR: 20-1)


78332 The region of interest localization for glaucoma analysis from retinal fundus image using deep learning
Setua SK
Computer Methods and Programs in Biomedicine 2018; 165: 25-35 (IGR: 20-1)


79160 Automated gonioscopy photography for iridocorneal angle grading
Neves CM
European Journal of Ophthalmology 2018; 0: 1120672118806436 (IGR: 20-1)


78765 Deep convolutional neural network-based patch classification for retinal nerve fiber layer defect detection in early glaucoma
Padhy D
Journal of medical imaging (Bellingham, Wash.) 2018; 5: 044003 (IGR: 20-1)


78813 Fundus image classification methods for the detection of glaucoma: A review
Raza M
Microscopy Research and Technique 2018; 81: 1105-1121 (IGR: 20-1)


78765 Deep convolutional neural network-based patch classification for retinal nerve fiber layer defect detection in early glaucoma
Panda G
Journal of medical imaging (Bellingham, Wash.) 2018; 5: 044003 (IGR: 20-1)


79157 Artificial intelligence and deep learning in ophthalmology
Raman R
British Journal of Ophthalmology 2019; 103: 167-175 (IGR: 20-1)


79160 Automated gonioscopy photography for iridocorneal angle grading
Pinto LA
European Journal of Ophthalmology 2018; 0: 1120672118806436 (IGR: 20-1)


79157 Artificial intelligence and deep learning in ophthalmology
Tan GSW; Schmetterer L; Keane PA; Wong TY
British Journal of Ophthalmology 2019; 103: 167-175 (IGR: 20-1)


78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Fu H
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605 (IGR: 19-4)


78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Hagiwara Y
Computer Methods and Programs in Biomedicine 2018; 165: 1-12 (IGR: 19-4)


78268 Deep learning in ophthalmology: a review
Grewal PS
Canadian Journal of Ophthalmology 2018; 53: 309-313 (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Devalla SK
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Kipli K
Computational and mathematical methods in medicine 2018; 2018: 4019538 (IGR: 19-4)


78241 Evaluation of Automated Segmentation Algorithms for Optic Nerve Head Structures in Optical Coherence Tomography Images
Duan XJ
Investigative Ophthalmology and Visual Science 2018; 59: 3816-3826 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Tanito M
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
An G
Journal of healthcare engineering 2018; 2018: 6874765 (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Renukanand PK
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Nitta K
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Omodaka K
Journal of healthcare engineering 2018; 2018: 6874765 (IGR: 19-4)


78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Koh JEW
Computer Methods and Programs in Biomedicine 2018; 165: 1-12 (IGR: 19-4)


78268 Deep learning in ophthalmology: a review
Oloumi F
Canadian Journal of Ophthalmology 2018; 53: 309-313 (IGR: 19-4)


78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Cheng J
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605 (IGR: 19-4)


78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Hoque ME
Computational and mathematical methods in medicine 2018; 2018: 4019538 (IGR: 19-4)


78241 Evaluation of Automated Segmentation Algorithms for Optic Nerve Head Structures in Optical Coherence Tomography Images
Jefferys JL
Investigative Ophthalmology and Visual Science 2018; 59: 3816-3826 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Katai M
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Xu Y
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605 (IGR: 19-4)


78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Lim LT
Computational and mathematical methods in medicine 2018; 2018: 4019538 (IGR: 19-4)


78241 Evaluation of Automated Segmentation Algorithms for Optic Nerve Head Structures in Optical Coherence Tomography Images
Quigley HA
Investigative Ophthalmology and Visual Science 2018; 59: 3816-3826 (IGR: 19-4)


78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Tsuda S
Journal of healthcare engineering 2018; 2018: 6874765 (IGR: 19-4)


78268 Deep learning in ophthalmology: a review
Rubin U
Canadian Journal of Ophthalmology 2018; 53: 309-313 (IGR: 19-4)


78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Tan JH
Computer Methods and Programs in Biomedicine 2018; 165: 1-12 (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Sreedhar BK
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Bhandary SV
Computer Methods and Programs in Biomedicine 2018; 165: 1-12 (IGR: 19-4)


78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Mahmood MH
Computational and mathematical methods in medicine 2018; 2018: 4019538 (IGR: 19-4)


78268 Deep learning in ophthalmology: a review
Tennant MTS
Canadian Journal of Ophthalmology 2018; 53: 309-313 (IGR: 19-4)


78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Wong DWK
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Kitaoka Y
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Subramanian G
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Shiga Y; Takada N
Journal of healthcare engineering 2018; 2018: 6874765 (IGR: 19-4)


78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Liu J
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605 (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Zhang L
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Laude A
Computer Methods and Programs in Biomedicine 2018; 165: 1-12 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Yokoyama Y
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Sahari SK
Computational and mathematical methods in medicine 2018; 2018: 4019538 (IGR: 19-4)


78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Cao X
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Omodaka K
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Ciaccio EJ
Computer Methods and Programs in Biomedicine 2018; 165: 1-12 (IGR: 19-4)


78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Kikawa T
Journal of healthcare engineering 2018; 2018: 6874765 (IGR: 19-4)


78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Sapawi R
Computational and mathematical methods in medicine 2018; 2018: 4019538 (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Perera S
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Rajaee N
Computational and mathematical methods in medicine 2018; 2018: 4019538 (IGR: 19-4)


78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Nakazawa T
Journal of healthcare engineering 2018; 2018: 6874765 (IGR: 19-4)


78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Tong L
Computer Methods and Programs in Biomedicine 2018; 165: 1-12 (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Mari JM
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Naito T
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Chin KS
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Yamashita T
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Joseph A
Computational and mathematical methods in medicine 2018; 2018: 4019538 (IGR: 19-4)


78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Acharya UR
Computer Methods and Programs in Biomedicine 2018; 165: 1-12 (IGR: 19-4)


78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Yokota H
Journal of healthcare engineering 2018; 2018: 6874765 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Mizoue S
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Tun TA
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Akiba M
Journal of healthcare engineering 2018; 2018: 6874765 (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Strouthidis NG
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Iwase A
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Aung T
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Nakazawa T
Acta Ophthalmologica 2018; 0: (IGR: 19-4)


78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Thiéry AH; Girard MJA
Biomedical optics express 2018; 9: 3244-3265 (IGR: 19-4)


77000 Comparison of changes of macular ganglion cell-inner plexiform layer defect between stable group and progression group in primary open-angle glaucoma
Seol BR
Japanese Journal of Ophthalmology 2018; 62: 491-498 (IGR: 19-3)


77317 Structure-preserving Guided Retinal Image Filtering and Its Application for Optic Disc Analysis
Cheng J
IEEE Transactions on Medical Imaging 2018; 0: (IGR: 19-3)


77058 A novel method for retinal optic disc detection using bat meta-heuristic algorithm
Abdullah AS
Medical and Biological Engineering and Computing 2018; 0: (IGR: 19-3)


77000 Comparison of changes of macular ganglion cell-inner plexiform layer defect between stable group and progression group in primary open-angle glaucoma
Yoo BW
Japanese Journal of Ophthalmology 2018; 62: 491-498 (IGR: 19-3)


77317 Structure-preserving Guided Retinal Image Filtering and Its Application for Optic Disc Analysis
Li Z
IEEE Transactions on Medical Imaging 2018; 0: (IGR: 19-3)


77058 A novel method for retinal optic disc detection using bat meta-heuristic algorithm
Özok YE; Rahebi J
Medical and Biological Engineering and Computing 2018; 0: (IGR: 19-3)


77317 Structure-preserving Guided Retinal Image Filtering and Its Application for Optic Disc Analysis
Gu Z
IEEE Transactions on Medical Imaging 2018; 0: (IGR: 19-3)


77000 Comparison of changes of macular ganglion cell-inner plexiform layer defect between stable group and progression group in primary open-angle glaucoma
Kim YK; Jeoung JW
Japanese Journal of Ophthalmology 2018; 62: 491-498 (IGR: 19-3)


77317 Structure-preserving Guided Retinal Image Filtering and Its Application for Optic Disc Analysis
Fu H
IEEE Transactions on Medical Imaging 2018; 0: (IGR: 19-3)


77000 Comparison of changes of macular ganglion cell-inner plexiform layer defect between stable group and progression group in primary open-angle glaucoma
Park KH
Japanese Journal of Ophthalmology 2018; 62: 491-498 (IGR: 19-3)


77317 Structure-preserving Guided Retinal Image Filtering and Its Application for Optic Disc Analysis
Wong DWK; Liu J
IEEE Transactions on Medical Imaging 2018; 0: (IGR: 19-3)


75175 Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects
Muhammad H
Journal of Glaucoma 2017; 26: 1086-1094 (IGR: 19-2)


75608 Automatic CDR Estimation for Early Glaucoma Diagnosis
Fernandez-Granero MA
Journal of healthcare engineering 2017; 2017: 5953621 (IGR: 19-2)


75480 A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis
Haleem MS
Journal of Medical Systems 2017; 42: 20 (IGR: 19-2)


75698 Fundus Densitometry Findings Suggest Optic Disc Hemorrhages in Primary Open-Angle Glaucoma Have an Arterial Origin
Chou JC
American Journal of Ophthalmology 2018; 187: 108-116 (IGR: 19-2)


75979 Analysis of inner and outer retinal layers using spectral domain optical coherence tomography automated segmentation software in ocular hypertensive and glaucoma patients
Cifuentes-Canorea P
PLoS ONE 2018; 13: e0196112 (IGR: 19-2)


75380 Optic disc segmentation for glaucoma screening system using fundus images
Almazroa A
Clinical Ophthalmology 2017; 11: 2017-2029 (IGR: 19-2)


75480 A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis
Han L
Journal of Medical Systems 2017; 42: 20 (IGR: 19-2)


75979 Analysis of inner and outer retinal layers using spectral domain optical coherence tomography automated segmentation software in ocular hypertensive and glaucoma patients
Ruiz-Medrano J
PLoS ONE 2018; 13: e0196112 (IGR: 19-2)


75380 Optic disc segmentation for glaucoma screening system using fundus images
Sun W
Clinical Ophthalmology 2017; 11: 2017-2029 (IGR: 19-2)


75698 Fundus Densitometry Findings Suggest Optic Disc Hemorrhages in Primary Open-Angle Glaucoma Have an Arterial Origin
Cousins CC
American Journal of Ophthalmology 2018; 187: 108-116 (IGR: 19-2)


75175 Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects
Fuchs TJ
Journal of Glaucoma 2017; 26: 1086-1094 (IGR: 19-2)


75608 Automatic CDR Estimation for Early Glaucoma Diagnosis
Sarmiento A
Journal of healthcare engineering 2017; 2017: 5953621 (IGR: 19-2)


75380 Optic disc segmentation for glaucoma screening system using fundus images
Alodhayb S
Clinical Ophthalmology 2017; 11: 2017-2029 (IGR: 19-2)


75175 Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects
De Cuir N
Journal of Glaucoma 2017; 26: 1086-1094 (IGR: 19-2)


75480 A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis
Hemert Jv
Journal of Medical Systems 2017; 42: 20 (IGR: 19-2)


75608 Automatic CDR Estimation for Early Glaucoma Diagnosis
Sanchez-Morillo D
Journal of healthcare engineering 2017; 2017: 5953621 (IGR: 19-2)


75698 Fundus Densitometry Findings Suggest Optic Disc Hemorrhages in Primary Open-Angle Glaucoma Have an Arterial Origin
Miller JB
American Journal of Ophthalmology 2018; 187: 108-116 (IGR: 19-2)


75979 Analysis of inner and outer retinal layers using spectral domain optical coherence tomography automated segmentation software in ocular hypertensive and glaucoma patients
Gutierrez-Bonet R
PLoS ONE 2018; 13: e0196112 (IGR: 19-2)


75698 Fundus Densitometry Findings Suggest Optic Disc Hemorrhages in Primary Open-Angle Glaucoma Have an Arterial Origin
Song BJ
American Journal of Ophthalmology 2018; 187: 108-116 (IGR: 19-2)


75608 Automatic CDR Estimation for Early Glaucoma Diagnosis
Jiménez S
Journal of healthcare engineering 2017; 2017: 5953621 (IGR: 19-2)


75979 Analysis of inner and outer retinal layers using spectral domain optical coherence tomography automated segmentation software in ocular hypertensive and glaucoma patients
Peña-Garcia P
PLoS ONE 2018; 13: e0196112 (IGR: 19-2)


75175 Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects
De Moraes CG
Journal of Glaucoma 2017; 26: 1086-1094 (IGR: 19-2)


75380 Optic disc segmentation for glaucoma screening system using fundus images
Raahemifar K
Clinical Ophthalmology 2017; 11: 2017-2029 (IGR: 19-2)


75480 A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis
Li B
Journal of Medical Systems 2017; 42: 20 (IGR: 19-2)


75608 Automatic CDR Estimation for Early Glaucoma Diagnosis
Alemany P
Journal of healthcare engineering 2017; 2017: 5953621 (IGR: 19-2)


75698 Fundus Densitometry Findings Suggest Optic Disc Hemorrhages in Primary Open-Angle Glaucoma Have an Arterial Origin
Shen LQ
American Journal of Ophthalmology 2018; 187: 108-116 (IGR: 19-2)


75380 Optic disc segmentation for glaucoma screening system using fundus images
Lakshminarayanan V
Clinical Ophthalmology 2017; 11: 2017-2029 (IGR: 19-2)


75480 A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis
Fleming A
Journal of Medical Systems 2017; 42: 20 (IGR: 19-2)


75979 Analysis of inner and outer retinal layers using spectral domain optical coherence tomography automated segmentation software in ocular hypertensive and glaucoma patients
Saenz-Frances F
PLoS ONE 2018; 13: e0196112 (IGR: 19-2)


75175 Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects
Blumberg DM
Journal of Glaucoma 2017; 26: 1086-1094 (IGR: 19-2)


75979 Analysis of inner and outer retinal layers using spectral domain optical coherence tomography automated segmentation software in ocular hypertensive and glaucoma patients
Garcia-Feijoo J
PLoS ONE 2018; 13: e0196112 (IGR: 19-2)


75480 A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis
Pasquale LR
Journal of Medical Systems 2017; 42: 20 (IGR: 19-2)


75175 Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects
Liebmann JM
Journal of Glaucoma 2017; 26: 1086-1094 (IGR: 19-2)


75698 Fundus Densitometry Findings Suggest Optic Disc Hemorrhages in Primary Open-Angle Glaucoma Have an Arterial Origin
Kass MA
American Journal of Ophthalmology 2018; 187: 108-116 (IGR: 19-2)


75608 Automatic CDR Estimation for Early Glaucoma Diagnosis
Fondón I
Journal of healthcare engineering 2017; 2017: 5953621 (IGR: 19-2)


75979 Analysis of inner and outer retinal layers using spectral domain optical coherence tomography automated segmentation software in ocular hypertensive and glaucoma patients
Martinez-de-la-Casa JM
PLoS ONE 2018; 13: e0196112 (IGR: 19-2)


75175 Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects
Ritch R
Journal of Glaucoma 2017; 26: 1086-1094 (IGR: 19-2)


75480 A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis
Song BJ
Journal of Medical Systems 2017; 42: 20 (IGR: 19-2)


75698 Fundus Densitometry Findings Suggest Optic Disc Hemorrhages in Primary Open-Angle Glaucoma Have an Arterial Origin
Wiggs JL; Pasquale LR
American Journal of Ophthalmology 2018; 187: 108-116 (IGR: 19-2)


75175 Hybrid Deep Learning on Single Wide-field Optical Coherence tomography Scans Accurately Classifies Glaucoma Suspects
Hood DC
Journal of Glaucoma 2017; 26: 1086-1094 (IGR: 19-2)


74722 Computer-aided diagnosis based on enhancement of degraded fundus photographs
Jin K
Acta Ophthalmologica 2018; 96: e320-e326 (IGR: 19-1)


74349 Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images
Sigut J
PeerJ 2017; 5: e3763 (IGR: 19-1)


74720 Optic Disc Image Subtraction as an Aid to Detect Glaucoma Progression
Amini N
Translational vision science & technology 2017; 6: 14 (IGR: 19-1)


74305 Morphometric parameters of the optic disc in normal and glaucomatous eyes based on time-domain optical coherence tomography image analysis
Buteikienė D
Medicina (Kaunas, Lithuania) 2017; 53: 242-252 (IGR: 19-1)


74669 Blood Vessel Extraction in Color Retinal Fundus Images with Enhancement Filtering and Unsupervised Classification
Yavuz Z
Journal of healthcare engineering 2017; 2017: 4897258 (IGR: 19-1)


74253 Similarity regularized sparse group lasso for cup to disc ratio computation
Cheng J
Biomedical optics express 2017; 8: 3763-3777 (IGR: 19-1)


74466 An Automatic Image Processing System for Glaucoma Screening
Almazroa A
International journal of biomedical imaging 2017; 2017: 4826385 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Miki A
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Sandhu S
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74720 Optic Disc Image Subtraction as an Aid to Detect Glaucoma Progression
Alizadeh R
Translational vision science & technology 2017; 6: 14 (IGR: 19-1)


74253 Similarity regularized sparse group lasso for cup to disc ratio computation
Zhang Z
Biomedical optics express 2017; 8: 3763-3777 (IGR: 19-1)


74349 Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images
Nunez O
PeerJ 2017; 5: e3763 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Kumoi M
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


74722 Computer-aided diagnosis based on enhancement of degraded fundus photographs
Zhou M
Acta Ophthalmologica 2018; 96: e320-e326 (IGR: 19-1)


74305 Morphometric parameters of the optic disc in normal and glaucomatous eyes based on time-domain optical coherence tomography image analysis
Kybartaitė-Žilienė A
Medicina (Kaunas, Lithuania) 2017; 53: 242-252 (IGR: 19-1)


74669 Blood Vessel Extraction in Color Retinal Fundus Images with Enhancement Filtering and Unsupervised Classification
Köse C
Journal of healthcare engineering 2017; 2017: 4897258 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Rudnisky C
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74466 An Automatic Image Processing System for Glaucoma Screening
Alodhayb S
International journal of biomedical imaging 2017; 2017: 4826385 (IGR: 19-1)


74722 Computer-aided diagnosis based on enhancement of degraded fundus photographs
Wang S
Acta Ophthalmologica 2018; 96: e320-e326 (IGR: 19-1)


74253 Similarity regularized sparse group lasso for cup to disc ratio computation
Tao D
Biomedical optics express 2017; 8: 3763-3777 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Arora S
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74466 An Automatic Image Processing System for Glaucoma Screening
Raahemifar K
International journal of biomedical imaging 2017; 2017: 4826385 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Usui S
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


74349 Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images
Fumero F
PeerJ 2017; 5: e3763 (IGR: 19-1)


74720 Optic Disc Image Subtraction as an Aid to Detect Glaucoma Progression
Parivisutt N
Translational vision science & technology 2017; 6: 14 (IGR: 19-1)


74305 Morphometric parameters of the optic disc in normal and glaucomatous eyes based on time-domain optical coherence tomography image analysis
Kriaučiūnienė L
Medicina (Kaunas, Lithuania) 2017; 53: 242-252 (IGR: 19-1)


74466 An Automatic Image Processing System for Glaucoma Screening
Lakshminarayanan V
International journal of biomedical imaging 2017; 2017: 4826385 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Endo T
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


74253 Similarity regularized sparse group lasso for cup to disc ratio computation
Wong DWK
Biomedical optics express 2017; 8: 3763-3777 (IGR: 19-1)


74349 Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images
Gonzalez M
PeerJ 2017; 5: e3763 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Kassam F
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74720 Optic Disc Image Subtraction as an Aid to Detect Glaucoma Progression
Kim E
Translational vision science & technology 2017; 6: 14 (IGR: 19-1)


74305 Morphometric parameters of the optic disc in normal and glaucomatous eyes based on time-domain optical coherence tomography image analysis
Barzdžiukas V
Medicina (Kaunas, Lithuania) 2017; 53: 242-252 (IGR: 19-1)


74722 Computer-aided diagnosis based on enhancement of degraded fundus photographs
Lou L
Acta Ophthalmologica 2018; 96: e320-e326 (IGR: 19-1)


74349 Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images
Arnay R
PeerJ 2017; 5: e3763 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Douglas G
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74305 Morphometric parameters of the optic disc in normal and glaucomatous eyes based on time-domain optical coherence tomography image analysis
Janulevičienė I
Medicina (Kaunas, Lithuania) 2017; 53: 242-252 (IGR: 19-1)


74720 Optic Disc Image Subtraction as an Aid to Detect Glaucoma Progression
Nouri-Mahdavi K
Translational vision science & technology 2017; 6: 14 (IGR: 19-1)


74722 Computer-aided diagnosis based on enhancement of degraded fundus photographs
Xu Y
Acta Ophthalmologica 2018; 96: e320-e326 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Kawashima R
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


74253 Similarity regularized sparse group lasso for cup to disc ratio computation
Liu J
Biomedical optics express 2017; 8: 3763-3777 (IGR: 19-1)


74305 Morphometric parameters of the optic disc in normal and glaucomatous eyes based on time-domain optical coherence tomography image analysis
Paunksnis A
Medicina (Kaunas, Lithuania) 2017; 53: 242-252 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Morimoto T
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Edwards MC
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74253 Similarity regularized sparse group lasso for cup to disc ratio computation
Baskaran M
Biomedical optics express 2017; 8: 3763-3777 (IGR: 19-1)


74722 Computer-aided diagnosis based on enhancement of degraded fundus photographs
Ye J
Acta Ophthalmologica 2018; 96: e320-e326 (IGR: 19-1)


74720 Optic Disc Image Subtraction as an Aid to Detect Glaucoma Progression
Caprioli J
Translational vision science & technology 2017; 6: 14 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Verstraten K
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74722 Computer-aided diagnosis based on enhancement of degraded fundus photographs
Qian D
Acta Ophthalmologica 2018; 96: e320-e326 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Matsushita K
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


74253 Similarity regularized sparse group lasso for cup to disc ratio computation
Aung T
Biomedical optics express 2017; 8: 3763-3777 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Wong B
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Fujikado T
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


74253 Similarity regularized sparse group lasso for cup to disc ratio computation
Wong TY
Biomedical optics express 2017; 8: 3763-3777 (IGR: 19-1)


74218 Compressed 3D and 2D digital images versus standard 3D slide film for the evaluation of glaucomatous optic nerve features
Damji KF
British Journal of Ophthalmology 2018; 102: 364-368 (IGR: 19-1)


74263 Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images
Nishida K
Journal of Glaucoma 2017; 26: 995-1000 (IGR: 19-1)


73004 Blood vessel segmentation in color fundus images based on regional and Hessian features
Shah SAA
Graefe's Archive for Clinical and Experimental Ophthalmology 2017; 255: 1525-1533 (IGR: 18-4)


72733 Diagnosis of retinal health in digital fundus images using continuous wavelet transform (CWT) and entropies
Koh JEW; Acharya UR
Computers in Biology and Medicine 2017; 84: 89-97 (IGR: 18-4)


73004 Blood vessel segmentation in color fundus images based on regional and Hessian features
Tang TB; Faye I
Graefe's Archive for Clinical and Experimental Ophthalmology 2017; 255: 1525-1533 (IGR: 18-4)


72733 Diagnosis of retinal health in digital fundus images using continuous wavelet transform (CWT) and entropies
Hagiwara Y
Computers in Biology and Medicine 2017; 84: 89-97 (IGR: 18-4)


73004 Blood vessel segmentation in color fundus images based on regional and Hessian features
Laude A
Graefe's Archive for Clinical and Experimental Ophthalmology 2017; 255: 1525-1533 (IGR: 18-4)


72733 Diagnosis of retinal health in digital fundus images using continuous wavelet transform (CWT) and entropies
Raghavendra U; Tan JH; Sree SV; Bhandary SV; Rao AK; Sivaprasad S; Chua KC; Laude A; Tong L
Computers in Biology and Medicine 2017; 84: 89-97 (IGR: 18-4)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Pradhan ZS
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71567 HIDDEN INFORMATION IN COLOR FUNDUS PHOTOGRAPHS IS REVEALED BY THE DECORRELATION STRETCHING METHOD
Uji A
Retinal cases & brief reports 2019; 13: 176-180 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Waisbourd M
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Rossi EA
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


71463 A Digital Staining Algorithm for Optical Coherence Tomography Images of the Optic Nerve Head
Mari JM; Aung T
Translational vision science & technology 2017; 6: 8 (IGR: 18-3)


71567 HIDDEN INFORMATION IN COLOR FUNDUS PHOTOGRAPHS IS REVEALED BY THE DECORRELATION STRETCHING METHOD
Muraoka Y
Retinal cases & brief reports 2019; 13: 176-180 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Granger CE
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Rao HL
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Gensure RH
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Puttaiah NK
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71463 A Digital Staining Algorithm for Optical Coherence Tomography Images of the Optic Nerve Head
Cheng CY
Translational vision science & technology 2017; 6: 8 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Aminlari A
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71567 HIDDEN INFORMATION IN COLOR FUNDUS PHOTOGRAPHS IS REVEALED BY THE DECORRELATION STRETCHING METHOD
Yoshimura N
Retinal cases & brief reports 2019; 13: 176-180 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Sharma R; Yang Q
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Shah SB
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Kadambi SV
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71463 A Digital Staining Algorithm for Optical Coherence Tomography Images of the Optic Nerve Head
Strouthidis NG
Translational vision science & technology 2017; 6: 8 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Khanna N
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Saito K
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


71463 A Digital Staining Algorithm for Optical Coherence Tomography Images of the Optic Nerve Head
Girard MJ
Translational vision science & technology 2017; 6: 8 (IGR: 18-3)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Dasari S
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Sood N
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Schwarz C
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Reddy HB
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Walters S
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Palakurthy M
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Molineaux J; Gonzalez A
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Riyazuddin M
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Nozato K
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Myers JS
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Zhang J
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


71456 Predicting the Magnitude of Functional and Structural Damage in Glaucoma From Monocular Pupillary Light Responses Using Automated Pupillography
Rao DA
Journal of Glaucoma 2017; 26: 409-414 (IGR: 18-3)


71609 Short-duration transient visual evoked potentials and color reflectivity discretization analysis in glaucoma patients and suspects
Katz LJ
International Journal of Ophthalmology 2017; 10: 254-261 (IGR: 18-3)


71225 Imaging individual neurons in the retinal ganglion cell layer of the living eye
Kawakami T; Fischer W; Latchney LR; Hunter JJ; Chung MM; Williams DR
Proceedings of the National Academy of Sciences of the United States of America 2017; 114: 586-591 (IGR: 18-3)


70304 Atlas-based shape analysis and classification of retinal optical coherence tomography images using the functional shape (fshape) framework
Lee S
Medical Image Analysis 2017; 35: 570-581 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Mastropasqua R
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70041 Glaucoma: the retina and beyond
Davis BM
Acta Neuropathologica 2016; 132: 807-826 (IGR: 18-2)


70747 Agreement in Measurement of Optic Cup-to-Disc Ratio with Stereo Biomicroscope Funduscopy and Digital Image Analysis: Results from the Nigeria National Blindness and Visual Impairment Survey
Kyari F
Ophthalmic Epidemiology 2017; 24: 57-62 (IGR: 18-2)


70617 Genetic and Environmental Factors Associated With the Ganglion Cell Complex in a Healthy Aging British Cohort
Bloch E
JAMA ophthalmology 2017; 135: 31-38 (IGR: 18-2)


70852 Retinal and choroidal oxygen saturation of the optic nerve head in open-angle glaucoma subjects by multispectral imaging
Li GY
Medicine 2016; 95: e5775 (IGR: 18-2)


70701 Detection of Glaucoma Using Image Processing Techniques: A Critique
Kumar BN
Seminars in Ophthalmology 2016; 0: 1-9 (IGR: 18-2)


70145 Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation
Zilly J
Computerized Medical Imaging and Graphics 2017; 55: 28-41 (IGR: 18-2)


70591 Ensemble Pruning for Glaucoma Detection in an Unbalanced Data Set
Adler W
Methods of Information in Medicine 2016; 55: 557-563 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Takada N
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70836 Multimodal registration of SD-OCT volumes and fundus photographs using histograms of oriented gradients
Miri MS
Biomedical optics express 2016; 7: 5252-5267 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Agnifili L
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70852 Retinal and choroidal oxygen saturation of the optic nerve head in open-angle glaucoma subjects by multispectral imaging
Al-Wesabi SA
Medicine 2016; 95: e5775 (IGR: 18-2)


70747 Agreement in Measurement of Optic Cup-to-Disc Ratio with Stereo Biomicroscope Funduscopy and Digital Image Analysis: Results from the Nigeria National Blindness and Visual Impairment Survey
Gilbert C
Ophthalmic Epidemiology 2017; 24: 57-62 (IGR: 18-2)


70836 Multimodal registration of SD-OCT volumes and fundus photographs using histograms of oriented gradients
Abràmoff MD
Biomedical optics express 2016; 7: 5252-5267 (IGR: 18-2)


70617 Genetic and Environmental Factors Associated With the Ganglion Cell Complex in a Healthy Aging British Cohort
Yonova-Doing E
JAMA ophthalmology 2017; 135: 31-38 (IGR: 18-2)


70041 Glaucoma: the retina and beyond
Crawley L
Acta Neuropathologica 2016; 132: 807-826 (IGR: 18-2)


70591 Ensemble Pruning for Glaucoma Detection in an Unbalanced Data Set
Gefeller O
Methods of Information in Medicine 2016; 55: 557-563 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Omodaka K
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70701 Detection of Glaucoma Using Image Processing Techniques: A Critique
Chauhan RP
Seminars in Ophthalmology 2016; 0: 1-9 (IGR: 18-2)


70145 Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation
Buhmann JM
Computerized Medical Imaging and Graphics 2017; 55: 28-41 (IGR: 18-2)


70304 Atlas-based shape analysis and classification of retinal optical coherence tomography images using the functional shape (fshape) framework
Charon N
Medical Image Analysis 2017; 35: 570-581 (IGR: 18-2)


70747 Agreement in Measurement of Optic Cup-to-Disc Ratio with Stereo Biomicroscope Funduscopy and Digital Image Analysis: Results from the Nigeria National Blindness and Visual Impairment Survey

Ophthalmic Epidemiology 2017; 24: 57-62 (IGR: 18-2)


70617 Genetic and Environmental Factors Associated With the Ganglion Cell Complex in a Healthy Aging British Cohort
Jones-Odeh E
JAMA ophthalmology 2017; 135: 31-38 (IGR: 18-2)


70304 Atlas-based shape analysis and classification of retinal optical coherence tomography images using the functional shape (fshape) framework
Charlier B
Medical Image Analysis 2017; 35: 570-581 (IGR: 18-2)


70852 Retinal and choroidal oxygen saturation of the optic nerve head in open-angle glaucoma subjects by multispectral imaging
Zhang H
Medicine 2016; 95: e5775 (IGR: 18-2)


70701 Detection of Glaucoma Using Image Processing Techniques: A Critique
Dahiya N
Seminars in Ophthalmology 2016; 0: 1-9 (IGR: 18-2)


70145 Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation
Mahapatra D
Computerized Medical Imaging and Graphics 2017; 55: 28-41 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Fasanella V
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70836 Multimodal registration of SD-OCT volumes and fundus photographs using histograms of oriented gradients
Kwon YH
Biomedical optics express 2016; 7: 5252-5267 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Kikawa T
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70041 Glaucoma: the retina and beyond
Pahlitzsch M
Acta Neuropathologica 2016; 132: 807-826 (IGR: 18-2)


70591 Ensemble Pruning for Glaucoma Detection in an Unbalanced Data Set
Gul A
Methods of Information in Medicine 2016; 55: 557-563 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Takagi A
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70591 Ensemble Pruning for Glaucoma Detection in an Unbalanced Data Set
Horn FK
Methods of Information in Medicine 2016; 55: 557-563 (IGR: 18-2)


70041 Glaucoma: the retina and beyond
Javaid F
Acta Neuropathologica 2016; 132: 807-826 (IGR: 18-2)


70304 Atlas-based shape analysis and classification of retinal optical coherence tomography images using the functional shape (fshape) framework
Popuri K
Medical Image Analysis 2017; 35: 570-581 (IGR: 18-2)


70836 Multimodal registration of SD-OCT volumes and fundus photographs using histograms of oriented gradients
Garvin MK
Biomedical optics express 2016; 7: 5252-5267 (IGR: 18-2)


70617 Genetic and Environmental Factors Associated With the Ganglion Cell Complex in a Healthy Aging British Cohort
Williams KM
JAMA ophthalmology 2017; 135: 31-38 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Lappa A
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70591 Ensemble Pruning for Glaucoma Detection in an Unbalanced Data Set
Khan Z
Methods of Information in Medicine 2016; 55: 557-563 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Matsumoto A
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70041 Glaucoma: the retina and beyond
Cordeiro MF
Acta Neuropathologica 2016; 132: 807-826 (IGR: 18-2)


70304 Atlas-based shape analysis and classification of retinal optical coherence tomography images using the functional shape (fshape) framework
Lebed E
Medical Image Analysis 2017; 35: 570-581 (IGR: 18-2)


70617 Genetic and Environmental Factors Associated With the Ganglion Cell Complex in a Healthy Aging British Cohort
Kozareva D
JAMA ophthalmology 2017; 135: 31-38 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Brescia L
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70591 Ensemble Pruning for Glaucoma Detection in an Unbalanced Data Set
Lausen B
Methods of Information in Medicine 2016; 55: 557-563 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Lanzini M
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70617 Genetic and Environmental Factors Associated With the Ganglion Cell Complex in a Healthy Aging British Cohort
Hammond CJ
JAMA ophthalmology 2017; 135: 31-38 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Yokoyama Y
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70304 Atlas-based shape analysis and classification of retinal optical coherence tomography images using the functional shape (fshape) framework
Sarunic MV; Trouvé A
Medical Image Analysis 2017; 35: 570-581 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Shiga Y
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Oddone F
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Maruyama K
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Perri P
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70304 Atlas-based shape analysis and classification of retinal optical coherence tomography images using the functional shape (fshape) framework
Beg MF
Medical Image Analysis 2017; 35: 570-581 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Takahashi H
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


70499 In Vivo Distribution of Corneal Epithelial Dendritic Cells in Patients With Glaucoma
Mastropasqua L
Investigative Ophthalmology and Visual Science 2016; 57: 5996-6002 (IGR: 18-2)


70083 OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients
Akiba M; Nakazawa T
PLoS ONE 2016; 11: e0160226 (IGR: 18-2)


69457 Incorporation of gradient vector flow field in a multimodal graph-theoretic approach for segmenting the internal limiting membrane from glaucomatous optic nerve head-centered SD-OCT volumes
Miri MS; Robles VA; Abràmoff MD; Kwon YH; Garvin MK
Computerized Medical Imaging and Graphics 2017; 55: 87-94 (IGR: 18-1)


67206 Automated Diagnosis of Glaucoma Using Empirical Wavelet Transform and Correntropy Features Extracted from Fundus Images
Maheshwari S
IEEE journal of biomedical and health informatics 2016; 0: (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Ji Y
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67544 Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images
Haleem MS
Journal of Medical Systems 2016; 40: 132 (IGR: 17-4)


67206 Automated Diagnosis of Glaucoma Using Empirical Wavelet Transform and Correntropy Features Extracted from Fundus Images
Pachori RB
IEEE journal of biomedical and health informatics 2016; 0: (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Zuo C
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67544 Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images
Han L; Hemert Jv
Journal of Medical Systems 2016; 40: 132 (IGR: 17-4)


67206 Automated Diagnosis of Glaucoma Using Empirical Wavelet Transform and Correntropy Features Extracted from Fundus Images
Acharya UR
IEEE journal of biomedical and health informatics 2016; 0: (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Lin M
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67544 Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images
Fleming A
Journal of Medical Systems 2016; 40: 132 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Zhang X; Li M
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67544 Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images
Pasquale LR
Journal of Medical Systems 2016; 40: 132 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Mi L
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67544 Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images
Silva PS
Journal of Medical Systems 2016; 40: 132 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Liu B
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67544 Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images
Song BJ
Journal of Medical Systems 2016; 40: 132 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Wen F
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67544 Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images
Aiello LP
Journal of Medical Systems 2016; 40: 132 (IGR: 17-4)


65813 Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey
Almazroa A
Journal of Ophthalmology 2015; 2015: 180972 (IGR: 17-3)


65808 Automated segmentation of optic disc in SD-OCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection
Wu M
Optics express 2015; 23: 31216-31229 (IGR: 17-3)


66574 Color Reflectivity Discretization Analysis of OCT Images in the Detection of Glaucomatous Nerve Fiber Layer Defects
Shah SB
Journal of Glaucoma 2016; 25: e346-e354 (IGR: 17-3)


65853 Segmentation of Retinal Blood Vessels Based on Cake Filter
Bao XR
BioMed research international 2015; 2015: 137024 (IGR: 17-3)


65915 Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs
Chakrabarty L
Journal of Glaucoma 2016; 25: 590-597 (IGR: 17-3)


66239 Automated imaging technologies for the diagnosis of glaucoma: a comparative diagnostic study for the evaluation of the diagnostic accuracy, performance as triage tests and cost-effectiveness (GATE study)
Azuara-Blanco A
Health Technol Assess 2016; 20: 1-168 (IGR: 17-3)


65808 Automated segmentation of optic disc in SD-OCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection
Leng T
Optics express 2015; 23: 31216-31229 (IGR: 17-3)


66239 Automated imaging technologies for the diagnosis of glaucoma: a comparative diagnostic study for the evaluation of the diagnostic accuracy, performance as triage tests and cost-effectiveness (GATE study)
Banister K
Health Technol Assess 2016; 20: 1-168 (IGR: 17-3)


65915 Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs
Joshi GD
Journal of Glaucoma 2016; 25: 590-597 (IGR: 17-3)


66574 Color Reflectivity Discretization Analysis of OCT Images in the Detection of Glaucomatous Nerve Fiber Layer Defects
Garcia AG
Journal of Glaucoma 2016; 25: e346-e354 (IGR: 17-3)


65853 Segmentation of Retinal Blood Vessels Based on Cake Filter
Ge X
BioMed research international 2015; 2015: 137024 (IGR: 17-3)


65813 Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey
Burman R
Journal of Ophthalmology 2015; 2015: 180972 (IGR: 17-3)


66574 Color Reflectivity Discretization Analysis of OCT Images in the Detection of Glaucomatous Nerve Fiber Layer Defects
Leiby BE
Journal of Glaucoma 2016; 25: e346-e354 (IGR: 17-3)


65853 Segmentation of Retinal Blood Vessels Based on Cake Filter
She LH
BioMed research international 2015; 2015: 137024 (IGR: 17-3)


65915 Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs
Chakravarty A
Journal of Glaucoma 2016; 25: 590-597 (IGR: 17-3)


65813 Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey
Raahemifar K
Journal of Ophthalmology 2015; 2015: 180972 (IGR: 17-3)


66239 Automated imaging technologies for the diagnosis of glaucoma: a comparative diagnostic study for the evaluation of the diagnostic accuracy, performance as triage tests and cost-effectiveness (GATE study)
Boachie C
Health Technol Assess 2016; 20: 1-168 (IGR: 17-3)


65808 Automated segmentation of optic disc in SD-OCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection
de Sisternes L
Optics express 2015; 23: 31216-31229 (IGR: 17-3)


65853 Segmentation of Retinal Blood Vessels Based on Cake Filter
Zhang S
BioMed research international 2015; 2015: 137024 (IGR: 17-3)


66574 Color Reflectivity Discretization Analysis of OCT Images in the Detection of Glaucomatous Nerve Fiber Layer Defects
Cox LA
Journal of Glaucoma 2016; 25: e346-e354 (IGR: 17-3)


65813 Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey
Lakshminarayanan V
Journal of Ophthalmology 2015; 2015: 180972 (IGR: 17-3)


66239 Automated imaging technologies for the diagnosis of glaucoma: a comparative diagnostic study for the evaluation of the diagnostic accuracy, performance as triage tests and cost-effectiveness (GATE study)
McMeekin P
Health Technol Assess 2016; 20: 1-168 (IGR: 17-3)


65808 Automated segmentation of optic disc in SD-OCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection
Rubin DL
Optics express 2015; 23: 31216-31229 (IGR: 17-3)


65915 Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs
Raman GV
Journal of Glaucoma 2016; 25: 590-597 (IGR: 17-3)


66239 Automated imaging technologies for the diagnosis of glaucoma: a comparative diagnostic study for the evaluation of the diagnostic accuracy, performance as triage tests and cost-effectiveness (GATE study)
Gray J
Health Technol Assess 2016; 20: 1-168 (IGR: 17-3)


66574 Color Reflectivity Discretization Analysis of OCT Images in the Detection of Glaucomatous Nerve Fiber Layer Defects
Katz LJ
Journal of Glaucoma 2016; 25: e346-e354 (IGR: 17-3)


65808 Automated segmentation of optic disc in SD-OCT images and cup-to-disc ratios quantification by patch searching-based neural canal opening detection
Chen Q
Optics express 2015; 23: 31216-31229 (IGR: 17-3)


65915 Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs
Krishnadas SR; Sivaswamy J
Journal of Glaucoma 2016; 25: 590-597 (IGR: 17-3)


66239 Automated imaging technologies for the diagnosis of glaucoma: a comparative diagnostic study for the evaluation of the diagnostic accuracy, performance as triage tests and cost-effectiveness (GATE study)
Burr J
Health Technol Assess 2016; 20: 1-168 (IGR: 17-3)


66574 Color Reflectivity Discretization Analysis of OCT Images in the Detection of Glaucomatous Nerve Fiber Layer Defects
Myers JS
Journal of Glaucoma 2016; 25: e346-e354 (IGR: 17-3)


66239 Automated imaging technologies for the diagnosis of glaucoma: a comparative diagnostic study for the evaluation of the diagnostic accuracy, performance as triage tests and cost-effectiveness (GATE study)
Bourne R; Garway-Heath D; Batterbury M; Hernández R; McPherson G; Ramsay C; Cook J
Health Technol Assess 2016; 20: 1-168 (IGR: 17-3)


61700 Optic disc detection and boundary extraction in retinal images
Basit A
Applied Optics 2015; 54: 3440-3447 (IGR: 17-1)


61693 Utility of retinal thickness analyzer in early diagnosis of glaucomatous damage
Arrico L
In vivo (Athens, Greece) 2015; 29: 385-390 (IGR: 17-1)


61700 Optic disc detection and boundary extraction in retinal images
Fraz MM
Applied Optics 2015; 54: 3440-3447 (IGR: 17-1)


61693 Utility of retinal thickness analyzer in early diagnosis of glaucomatous damage
Nebbioso M; Komaiha C; Malagola R
In vivo (Athens, Greece) 2015; 29: 385-390 (IGR: 17-1)


60779 Optic disc segmentation by balloon snake with texture from color fundus image
Sun J
International journal of biomedical imaging 2015; 2015: 528626 (IGR: 16-4)


60755 Automated Registration of Multimodal Optic Disc Images: Clinical Assessment of Alignment Accuracy
Ng WS
Journal of Glaucoma 2016; 25: 397-402 (IGR: 16-4)


60274 Automated segmentation of the lamina cribrosa using Frangi's filter: a novel approach for rapid identification of tissue volume fraction and beam orientation in a trabeculated structure in the eye
Campbell IC; Coudrillier B
Journal of the Royal Society, Interface / the Royal Society 2015; 12: 20141009 (IGR: 16-4)


60779 Optic disc segmentation by balloon snake with texture from color fundus image
Luan F
International journal of biomedical imaging 2015; 2015: 528626 (IGR: 16-4)


60755 Automated Registration of Multimodal Optic Disc Images: Clinical Assessment of Alignment Accuracy
Legg P
Journal of Glaucoma 2016; 25: 397-402 (IGR: 16-4)


60274 Automated segmentation of the lamina cribrosa using Frangi's filter: a novel approach for rapid identification of tissue volume fraction and beam orientation in a trabeculated structure in the eye
Mensah J
Journal of the Royal Society, Interface / the Royal Society 2015; 12: 20141009 (IGR: 16-4)


60755 Automated Registration of Multimodal Optic Disc Images: Clinical Assessment of Alignment Accuracy
Avadhanam V
Journal of Glaucoma 2016; 25: 397-402 (IGR: 16-4)


60779 Optic disc segmentation by balloon snake with texture from color fundus image
Wu H
International journal of biomedical imaging 2015; 2015: 528626 (IGR: 16-4)


60755 Automated Registration of Multimodal Optic Disc Images: Clinical Assessment of Alignment Accuracy
Aye K
Journal of Glaucoma 2016; 25: 397-402 (IGR: 16-4)


60274 Automated segmentation of the lamina cribrosa using Frangi's filter: a novel approach for rapid identification of tissue volume fraction and beam orientation in a trabeculated structure in the eye
Abel RL; Ethier CR
Journal of the Royal Society, Interface / the Royal Society 2015; 12: 20141009 (IGR: 16-4)


60755 Automated Registration of Multimodal Optic Disc Images: Clinical Assessment of Alignment Accuracy
Evans SH; North RV; Marshall AD; Rosin P; Morgan JE
Journal of Glaucoma 2016; 25: 397-402 (IGR: 16-4)


59621 Robust multi-scale superpixel classification for optic cup localization
Tan NM; Xu Y; Goh WB; Liu J
Computerized Medical Imaging and Graphics 2015; 40: 182-193 (IGR: 16-3)


59211 Normative Databases for Imaging Instrumentation
Realini T; Zangwill LM; Flanagan JG; Garway-Heath D; Patella VM; Johnson CA; Artes PH; Gaddie IB; Fingeret M
Journal of Glaucoma 2015; 24: 480-483 (IGR: 16-3)


57360 Thickness related textural properties of retinal nerve fiber layer in color fundus images
Odstrcilik J; Kolar R; Tornow RP; Jan J; Budai A; Mayer M; Vodakova M; Laemmer R; Lamos M; Kuna Z; Gazarek J; Kubena T; Cernosek P; Ronzhina M
Computerized Medical Imaging and Graphics 2014; 38: 508-516 (IGR: 16-2)


57521 Detecting abnormality in optic nerve head images using a feature extraction analysis
Zhu H; Poostchi A; Vernon SA; Crabb DP
Biomedical optics express 2014; 5: 2215-2230 (IGR: 16-2)


57035 Phenotypic heterogeneity of corneal endothelium in iridocorneal endothelial syndrome by in vivo confocal microscopy
Malhotra C; Pandav SS; Gupta A; Jain AK
Cornea 2014; 33: 634-637 (IGR: 16-2)


56544 Use of macular thickness parameters for the diagnosis of primary open-angle glaucoma
Polaczek-Krupa B; Grabska-Liberek I; Kamiński M
Archives of Medical Science 2014; 10: 104-109 (IGR: 16-1)


56151 Tracing retinal vessel trees by transductive inference
De J; Li H; Cheng L
BMC bioinformatics 2014; 15: 20 (IGR: 16-1)


55335 In vivo confocal microscopy of the ocular surface: from bench to bedside
Villani E; Baudouin C; Efron N; Hamrah P; Kojima T; Patel SV; Pflugfelder SC; Zhivov A; Dogru M
Current Eye Research 2014; 39: 213-231 (IGR: 15-4)


55176 Intraobserver and interobserver agreement of computer software-assisted optic nerve head photoplanimetry
Tanito M; Sagara T; Takamatsu M; Kiuchi Y; Nakagawa T; Fujita Y; Ohira A
Japanese Journal of Ophthalmology 2014; 58: 56-61 (IGR: 15-4)


54563 Orbscan topography in primary open-angle glaucoma
Arranz-Marquez E; Bolivar G; Piñ,ero DP; Konstas AG; Mikropoulos DG; Teus MA
Optometry and Vision Science 2013; 90: 1098-1103 (IGR: 15-3)


54822 Automated anterior chamber angle localization and glaucoma type classification in OCT images
Xu Y; Liu J; Cheng J; Lee BH; Wong DW; Baskaran M; Perera S; Aung T
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2013; 2013: 7380-7383 (IGR: 15-3)


54820 Self-assessment for optic disc segmentation
Cheng J; Liu J; Yin F; Lee BH; Wong DW; Aung T; Cheng CY; Wong TY
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2013; 2013: 5861-5864 (IGR: 15-3)


54836 Automatic extraction of retinal features from colour retinal images for glaucoma diagnosis: A review
Haleem MS; Han L; van Hemert J; Li B
Computerized Medical Imaging and Graphics 2013; 37: 581-596 (IGR: 15-3)


54821 Automatic screening of narrow anterior chamber angle and angle-closure glaucoma based on slit-lamp image analysis by using support vector machine
Theeraworn C; Kongprawechnon W; Kondo T; Bunnun P; Nishihara A; Manassakorn A
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2013; 2013: 5887-5890 (IGR: 15-3)


54043 Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map
Kafieh R; Rabbani H; Abramoff MD; Sonka M
Medical Image Analysis 2013; 17: 907-928 (IGR: 15-2)


52937 Automated detection of optic disk in retinal fundus images using intuitionistic fuzzy histon segmentation
Mookiah MR; Acharya UR; Chua CK; Min LC; Ng EY; Mushrif MM; Laude A
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine 2013; 227: 37-49 (IGR: 15-1)


52477 The potential of annexin-labelling for the diagnosis and follow-up of glaucoma
Normando EM; Turner LA; Cordeiro MF
Cell and Tissue Research 2013; 353: 279-285 (IGR: 15-1)


53066 Comparison of disc analysis algorithms provided by cirrus OCT and stereo optic-disc photography in normal and open angle glaucoma patients
Lee M; Yoo H; Ahn J
Current Eye Research 2013; 38: 605-613 (IGR: 15-1)


52378 Optical properties of retinal tissue and the potential of adaptive optics to visualize retinal ganglion cells in vivo
Prasse M; Rauscher FG; Wiedemann P; Reichenbach A; Francke M
Cell and Tissue Research 2013; 353: 269-278 (IGR: 15-1)


52383 Automatic glaucoma diagnosis through medical imaging informatics
Liu J; Zhang Z; Wong DW; Xu Y; Yin F; Cheng J; Tan NM; Kwoh CK; Xu D; Tham YC; Aung T; Wong TY
Journal of the American Medical Informatics Association : JAMIA 2013; 20: 1021-1027 (IGR: 15-1)


52505 Superpixel classification based optic disc and optic cup segmentation for glaucoma screening
Cheng J; Liu J; Xu Y; Yin F; Wong DW; Tan NM; Tao D; Cheng CY; Aung T; Wong TY
IEEE Transactions on Medical Imaging 2013; 32: 1019-1032 (IGR: 15-1)


51768 Retinal image registration and comparison for clinical decision support
Xiao D; Vignarajan J; Lock J; Frost S; Tay-Kearney ML; Kanagasingam Y
The Australasian medical journal 2012; 5: 507-512 (IGR: 14-4)


51287 Peripapillary atrophy detection by sparse biologically inspired feature manifold
Cheng J; Tao D; Liu J; Wong DW; Tan NM; Wong TY; Saw SM
IEEE Transactions on Medical Imaging 2012; 31: 2355-2365 (IGR: 14-3)


51319 Retinal Vascular Geometry and Glaucoma: The Singapore Malay Eye Study
Wu R; Cheung CY; Saw SM; Mitchell P; Aung T; Wong TY
Ophthalmology 2013; 120: 77-83 (IGR: 14-3)


51288 Novel Fractal Feature-Based Multiclass Glaucoma Detection and Progression Prediction
Iftekharuddin K; Kim Y; Davey P; Essock E; Garas A; Hollo G
IEEE transactions on information technology in biomedicine: a publication of the IEEE Engineering in Medicine and Biology Society 2012; 0: (IGR: 14-3)


50618 Multimodal Retinal Vessel Segmentation from Spectral-Domain Optical Coherence Tomography and Fundus Photography
Hu Z; Niemeijer M; Abramoff M; Garvin M
IEEE Transactions on Medical Imaging 2012; 31: 1900-1911 (IGR: 14-2)


50201 Anterior visual pathway assessment by magnetic resonance imaging in normal-pressure glaucoma
Zhang YQ; Li J; Xu L; Zhang L; Wang ZC; Yang H; Chen CX; Wu XS; Jonas JB
Acta Ophthalmologica 2012; 90: e295-e302 (IGR: 14-2)


48702 Wavelet-based energy features for glaucomatous image classification
Dua S; Acharya UR; Chowriappa P; Sree SV
IEEE transactions on information technology in biomedicine: a publication of the IEEE Engineering in Medicine and Biology Society 2012; 16: 80-87 (IGR: 14-1)


49042 Depth discontinuity-based cup segmentation from multi-view colour retinal images
Joshi G; Sivaswamy J; Krishnadas S
IEEE Transactions on Bio-Medical Engineering 2012; 59: 1523-1531 (IGR: 14-1)


47985 Diffusion tensor imaging detects retinal ganglion cell axon damage in the mouse model of optic nerve crush
Zhang X; Sun P; Wang J; Wang Q; Song SK
Investigative ophthalmology & visual science 2011; 52: 7001-7006 (IGR: 13-4)


48142 Relationships between Visual Field Sensitivity and Spectral Absorption Properties of the Neuroretinal Rim in Glaucoma by Multispectral Imaging
Denniss J; Schiessl I; Nourrit V; Fenerty CH; Gautam R; Henson DB
Investigative Ophthalmology and Visual Science 2011; 52: 8732-8738 (IGR: 13-4)


48256 Macular ganglion cell layer imaging in preperimetric glaucoma with speckle noise-reduced spectral domain optical coherence tomography
Nakano N; Hangai M; Nakanishi H; Mori S; Nukada M; Kotera Y; Ikeda HO; Nakamura H; Nonaka A; Yoshimura N
Ophthalmology 2011; 118: 2414-2426 (IGR: 13-4)


47882 Magnetic resonance in studies of glaucoma
Fiedorowicz M; Dyda W; Rejdak R; Grieb P
Medical Science Monitor 2011; 17: RA227-RA232 (IGR: 13-4)


47991 Optic disk and cup segmentation from monocular color retinal images for glaucoma assessment
Joshi GD; Sivaswamy J; Krishnadas SR
IEEE Transactions on Medical Imaging 2011; 30: 1192-1205 (IGR: 13-4)


47998 Statistical techniques for detection of optic disc and macula and parameters measurement in retinal fundus images
Kose C; Ikibas C
Journal of Medical and Biological Engineering 2011; 31: 395-404 (IGR: 13-4)


48049 Sliding window and regression based cup detection in digital fundus images for glaucoma diagnosis
Xu Y; Xu D; Lin S; Liu J; Cheng J; Cheung CY; Aung T; Wong TY
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention 2011; 14-3: 1-8 (IGR: 13-4)


48367 Visualization of the trabeculo-Descemet membrane in deep sclerectomy after Nd:YAG goniopuncture: an in vivo confocal microscopy study
Mansouri K; Mendrinos E; Shaarawy T; Dosso AA
Archives of Ophthalmology 2011; 129: 1305-1310 (IGR: 13-4)


48127 Suboptimal image focus broadens retinal vessel caliber measurement
Chandler CS; Gangaputra S; Hubbard LD; Ferrier NJ; Pauli TW; Peng Q; Thayer DW; Danis RP Jr
Investigative Ophthalmology and Visual Science 2011; 52: 8558-8561 (IGR: 13-4)


46239 Closed angle glaucoma detection in RetCam images
Cheng J; Liu J; Lee BH; Wong DW; Yin F; Aung T; Baskaran M; Shamira P; Yin Wong T
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2010; 2010: 4096-4099 (IGR: 13-2)


46087 FloatingCanvas: quantification of 3D retinal structures from spectral-domain optical coherence tomography
Zhu H; Crabb DP; Schlottmann PG; Ho T; Garway-Heath DF
Optics express 2010; 18: 24595-24610 (IGR: 13-2)


46234 Automatic blood vessel localization in small field of view eye images
Bansal M; Kuthirummal S; Eledath J; Sawhney H; Stone R
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2010; 2010: 5644-5648 (IGR: 13-2)


46312 A machine vision method for automated alignment of fundus imaging systems
Moscaritolo M; Knezevich 3rd FP; Zimmer-Galler I; Jampel H; Zeimer R
Ophthalmic surgery, lasers & imaging : the official journal of the International Society for Imaging in the Eye 2010; 41: 607-613 (IGR: 13-2)


46235 Mixture model-based approach for optic cup segmentation
Tan NM; Liu J; Wong DK; Yin F; Lim JH; Wong TY
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2010; 2010: 4817-4820 (IGR: 13-2)


46032 Morphometric analysis and classification of glaucomatous optic neuropathy using radial polynomials
Twa MD; Parthasarathy S; Johnson CA; Bullimore MA
Journal of Glaucoma 2011; (IGR: 13-2)


46238 ORIGA(-light): an online retinal fundus image database for glaucoma analysis and research
Zhang Z; Yin FS; Liu J; Wong WK; Tan NM; Lee BH; Cheng J; Wong TY
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2010; 2010: 3065-3068 (IGR: 13-2)


27942 Automated segmentation of optic disc region on retinal fundus photographs: Comparison of contour modeling and pixel classification methods
Muramatsu C; Nakagawa T; Sawada A; Hatanaka Y; Hara T; Yamamoto T; Fujita H
Computer Methods and Programs in Biomedicine 2011; 101: 23-32 (IGR: 13-1)


27786 Outer retinal abnormalities associated with inner retinal pathology in nonglaucomatous and glaucomatous optic neuropathies
Werner JS; Keltner JL; Zawadzki RJ; Choi SS
Eye 2011; 25: 279-89 (IGR: 13-1)


27836 Evidence of outer retinal changes in glaucoma patients as revealed by ultrahigh-resolution in vivo retinal imaging
Choi SS; Zawadzki RJ; Lim MC; Brandt JD; Keltner JL; Doble N; Werner JS
British Journal of Ophthalmology 2011; 95: 131-141 (IGR: 13-1)


28017 Postsurgical Imaging of the Globe
Swanger RS; Crum AV; Klett ZG; Bokhari SAJ
Seminars in Ultrasound, CT and MRI 2011; 32: 57-63 (IGR: 13-1)


26443 A geometric morphometric assessment of the optic cup in glaucoma
Sanfilippo PG; Cardini A; Sigal IA; Ruddle JB; Chua BE; Hewitt AW; Mackey DA
Experimental Eye Research 2010; 91: 405-414 (IGR: 12-3)


26516 Neuro-imaging examination of glaucomatous visual field defects
Yoshida M; Boucard CC; Hernowo AT; Ida M; Nishio T; Nishimoto F; Kato M; Nguyen Th; Istoc A; Iba-Zizen MT
Neuro-Ophthalmology 2010; 34: 180-181 (IGR: 12-3)


26465 Changes of the retinal thickness in the macula region in primary open-angle glaucoma patients measured with RTA analyzer
Polaczek-Krupa B; Grabska-Liberek I
Klinika Oczna 2010; 112: 24-28 (IGR: 12-3)


24301 The segmentation of zones with increased autofluorescence in the junctional zone of parapapillary atrophy
Kolar R; Laemmer R; Jan J; Mardin CY
Physiological Measurement 2009; 30: 505-516 (IGR: 11-3)


24131 Automated quality evaluation of digital fundus photographs
Bartling H; Wanger P; Martin L
Acta Ophthalmologica 2009; 87: 643-647 (IGR: 11-3)


24130 Effects of latanoprost in iris bioidentification
Lamminen H; Voipio V; Manninen T; Huttunen H
Acta Ophthalmologica 2009; 87: 529-531 (IGR: 11-3)


23586 Snapshot polarimeter fundus camera
DeHoog E; Luo H; Oka K; Dereniak E; Schwiegerling J
Applied Optics 2009; 48: 1663-1667 (IGR: 11-2)


22529 In-vivo confocal microscopy of iridocorneal endothelial syndrome
Le QH; Sun XH; Xu JJ
International Ophthalmology 2009; 29: 11-18 (IGR: 11-1)


22892 Clinical application of MRI in ophthalmology
Townsend KA; Wollstein G; Schuman JS
NMR in Biomedicine 2008; 21: 997-1002 (IGR: 11-1)


22891 Assessing optic nerve pathology with diffusion MRI: From mouse to human
Xu J; Sun S-W; Naismith RT; Snyder AZ; Cross AH; Song S-K
NMR in Biomedicine 2008; 21: 928-940 (IGR: 11-1)


21790 Estimation of ocular rigidity based on measurement of pulse amplitude using pneumotonometry and fundus pulse using laser interferometry in glaucoma
Hommer A; Fuchsjńger-Mayrl G; Resch H; Vass C; Garhofer G; Schmetterer L
Investigative Ophthalmology and Visual Science 2008; 49: 4046-4050 (IGR: 10-3)


21513 Relationship between the retinal thickness analyzer and the GDx VCC scanning laser polarimeter, Stratus OCT optical coherence tomograph, and Heidelberg Retina Tomograph II confocal scanning laser ophthalmoscopy
Ma KT; Lee SH; Hong S; Park KS; Kim CY; Seong GJ; Hong YJ
Korean Journal of Ophthalmology 2008; 22: 10-17 (IGR: 10-3)


21500 Identification of the optic nerve head with genetic algorithms
Carmona EJ; Rincon M; Garcia-Feijoo J; Martinez-de-la-Casa JM
Artificial Intelligence in Medicine 2008; 43: 243-259 (IGR: 10-3)


21557 Computer support for early glaucoma diagnosis based on the fused retinal images
Kolar R; Jan J; Kubecka L
Scripta Medica Facultatis Medicae Universitatis Brunensis Masarykianae 2006; 79: 249-260 (IGR: 10-3)


21360 3D vs 2D qualitative and semiquantitative evaluation of the glaucomatous optic disc atrophy using computer-assisted stereophotography
Lehmann MV; Mardin CY; Martus P; Bergua A
Eye 2008; 22: 628-635 (IGR: 10-2)


21381 Automated assessment of the optic nerve head on stereo disc photographs
Xu J; Ishikawa H; Wollstein G; Bilonick RA; Sung KR; Kagemann L; Townsend KA; Schuman JS
Investigative Ophthalmology and Visual Science 2008; 49: 2512-2517 (IGR: 10-2)


21241 Elastic registration for auto-fluorescence image averaging
Kubecka L; Jan J; Kolar R; Jirik R
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2006; 1: 1948-1951 (IGR: 10-2)


21235 Segmentation of optic nerve head using warping and RANSAC
Kim SK; Kong HJ; Seo JM; Cho BJ; Park KH; Hwang JM; Kim DM; Chung H; Kim HC
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2007; 2007: 900-903 (IGR: 10-2)


21245 Three-dimensional reconstruction of optic nerve head from stereo fundus images and its quantitative estimation
Nakagawa T; Hayashi Y; Hatanaka Y; Aoyama A; Hara T; Fujita A; Kakogawa M; Fujita H; Yamamoto T
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2007; 2007: 6748-6751 (IGR: 10-2)


21420 Functional in vivo assessment of retinal artery microirregularities in glaucoma
Kotliar KE; Nagel E; Vilser W; Lanzl IM
Acta Ophthalmologica 2008; 86: 424-433 (IGR: 10-2)


21237 Preliminary study on the association of vessel diameter variation and glaucoma
Vlachokosta AA; Asvestas PA; Matsopoulos GK; Uzunoglu N; Zeyen TG
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2007; 2007: 888-891 (IGR: 10-2)


21213 Software-assisted optic nerve assessment for glaucoma telescreening
Khouri AS; Szirth BC; Shahid KS; Fechtner RD
Telemedicine Journal and E-Health: the Official Journal of the American Telemedicine Association 2008; 14: 261-265 (IGR: 10-2)


20580 DARC: A new method for detecting progressive neuronal death
Cordeiro MF
Eye 2007; 21: S15-S17 (IGR: 10-1)


20577 Correlating nerve fibre layer defects spatially with functional loss
Schiefer U; Paetzold J; Krapp E; Nevalainen J; Besch D
Eye 2007; 21: S25-S28 (IGR: 10-1)


20579 High-resolution imaging of retinal cells in the living eye
Paques M; Simonutti M; Roux MJ; Bellman C; Lacombe F; Grieve K; Glanc M; LeMer Y; Sahel J-A
Eye 2007; 21: S18-S20 (IGR: 10-1)


20528 Spatiotemporal independent component analysis for the detection of functional responses in cat retinal images.
Barriga ES; Pattichis M; Ts'o D; Abramoff M; Kardon R; Kwon Y; Soliz P
IEEE Transactions on Medical Imaging 2007; 26: 1035-1045 (IGR: 10-1)


20562 Detection of glaucomatous change based on vessel shape analysis
Matsopoulos GK; Asvestas PA; Delibasis KK; Mouravliansky NA; Zeyen TG
Computerized Medical Imaging and Graphics 2008; 32: 183-192 (IGR: 10-1)


19704 Reconstruction segmentation and measurement of the color optic cup and disk image of optic nerve heads based on hierarchical Mumford-Shah model
Liu G-C; Wang Y-N; Quan H-M
Chinese Journal of Biomedical Engineering 2007; 26: 700-707+712 (IGR: 9-4)


19360 Application of second harmonic imaging microscopy to assess structural changes in optic nerve head structure ex vivo
Brown DJ; Morishige N; Neekhra A; Minckler DS; Jester JV
Journal of biomedical Optics 2007; 12: 24-29 (IGR: 9-3)


14534 Auto-adjusted 3-D optic disk viewing from low-resolution stereo fundus image
Xu J; Chutatape O
Computers in Biology and Medicine 2006; 36: 921-940 (IGR: 8-4)


14809 Influence of myelinated retinal nerve fibers on scanning laser polarimetry using variable and enhanced corneal compensation methods
Toth M; Hollo G
Ophthalmic Surgery Lasers and Imaging 2006; 37: 336-340 (IGR: 8-4)


15257 Novel approach for anterior chamber angle analysis: anterior chamber angle detection with edge measurement and identification algorithm (ACADEMIA)
Leung CK; Yung WH; Yiu CK; Lam SW; Leung DY; Tse RK; Tham CC; Chan WM; Lam DS
Archives of Ophthalmology 2006; 124: 1395-1401 (IGR: 8-4)


14260 MR imaging of optic nerve; relationship between signal intensity of the optic nerve at MR imaging and degrees of optic disc excavation
Kurokawa H; Kimu S; Otsuji T; Hatano H; Miyashiro M; Ikeda K; Omura N; Sawada H; Ogata N
Japanese Journal of Clinical Radiology 2006; 51: 515-519 (IGR: 8-3)


14018 Diagnostic accuracy of the Retinal Thickness Analyser: differentiation between normal eyes and eyes with glaucoma or macular pathologies
Maier P; Funk J
Graefe's Archive for Clinical and Experimental Ophthalmology 2006; 244: 1113-1118 (IGR: 8-3)


14133 Clinical study of anterior ocular segment topography in angle-closure glaucoma using the three-dimensional anterior segment analyzer Pentacam
Oka N; Otori Y; Okada M; Miki A; Maeda N; Tano Y
Nippon Ganka Gakkai Zasshi 2006; 110: 398-403 (IGR: 8-3)


13406 Repeatability and reproducibility of optic nerve head topography using the retinal thickness analyzer
Hoffmann EM; Medeiros FA; Kramann C; Pfeiffer N; Grus FH
Graefe's Archive for Clinical and Experimental Ophthalmology 2006; 244: 192-198 (IGR: 8-1)


13153 Age effect on retina and optic disc normal values
Neubauer AS; Chryssafis C; Thiel M; Tsinopoulos I; Hirneiss C; Kampik A
Ophthalmic Research 2005; 37: 243-249 (IGR: 7-3)


12552 Adaptive optics ophthalmoscopy: Results and applications
Pallikaris A
Journal of Refractive Surgery 2005; 21: S570-S574 (IGR: 7-3)


11382 Retinal thickness at the posterior pole in glaucoma and ocular hypertension
Cvenkel B
Graefe's Archive for Clinical and Experimental Ophthalmology 2004; 242: 920-925 (IGR: 6-3)


10697 Association of magnetic resonance imaging of anterior optic pathway with glaucomatous visual field damage and optic disc cupping
Kashiwagi K; Okubo T; Tsukahara S
Journal of Glaucoma 2004; 13:189-95 (IGR: 6-2)


10242 Reduction of posterior pole retinal thickness in glaucoma detected using the Retinal Thickness Analyzer
Tanito M; Itai N; Ohira A; Chihara E
Ophthalmology 2004; 111: 265-275 (IGR: 6-1)


9100 Digital stereo image analyzer for generating automated 3-D measures of optic disc deformation in glaucoma
Corona E; Mitra S; Wilson M; Krile T; Kwon YH; Soliz P
IEEE Transactions on Medical Imaging 2002; 21: 1244-1253 (IGR: 5-2)


8587 Correlation among retinal thickness, optic disc, and visual field in glaucoma patients and suspects: a pilot study
Asrani S; Challa P; Herndon LW; Lee PP; Stinnett S; Allingham RR
Journal of Glaucoma 2003; 12: 119-128 (IGR: 5-1)


8679 Comparison of optic disc topography measured by Retinal Thickness Analyzer with measurement by Heidelberg Retina Tomograph II
Itai N; Tanito M; Chihara E
Japanese Journal of Ophthalmology 2003; 47: 214-220 (IGR: 5-1)


8232 Orbscan: a new device for iridocorneal angle measurement
Allouch C; Touzeau O; Borderie V; Puech M; Ameline B; Scheer S; Laroche L
Journal Franšais d'Ophtalmologie 2002; 25: 799-806 (IGR: 4-3)


3436 The Autocad system for planimetric study of the optic disc in glaucoma: technique and reproducibility study
Sanchez Perez A; Honrubia Lopez FM; Larrosa Poves JM; Polo Llorens V; Melcon Sanchez Frieras B
Archivos de la Sociedad Espa˝ola de Oftalmologia 2001; 76: 551-558 (IGR: 4-2)


6747 Clinician change detection viewing longitudinal stereophotographs compared to confocal scanning laser tomography in the LSU Experimental Glaucoma (LEG) Study
Ervin JC; Lemij HG; Mills RP; Quigley HA; Thompson HW; Burgoyne CF
Ophthalmology 2002; 109: 467-481 (IGR: 4-1)


6750 Functional magnetic resonance imaging of the visual system
Miki A; Liu GT; Modestino EJ; Liu CSJ; Bonhomme GR; Dobre CM; Haselgrove JC
Current Opinions in Ophthalmology 2001; 12: 423-431 (IGR: 4-1)


15985 Measurement of human retinal thickness at the posterior pole with a retinal thickness analyzer in normal and glaucomatous eyes
Yang Z; Du S
Chinese Journal of Ophthalmology 2000; 36: 124 (IGR: 2-3)


15697 Detection of changes of the optic disc in glaucomatous eyes: clinical examination and image analysis with the Topcon Imagenet system
Azuara-Blanco A; Katz LJ; Spaeth GL; Nicholl J; Lanzl IM
Acta Ophthalmologica Scandinavica 2000; 78: 647-650 (IGR: 2-3)


5604 Digital imaging and microtexture analysis of the nerve fiber layer
Tuulonen A; Alanko H; Hyytinen P; Veijola J; Seppaenen T; Airaksinen PJ
Journal of Glaucoma 2000; 9:5-9 (IGR: 2-1)


5215 STIR sequences in magnetic resonance imaging for confirmation of optic nerve atrophy
Fischel JD; Garrett J; Bell J
Annals of Ophthalmology - Glaucoma 1999; 31: 153-155 (IGR: 1-2)


5217 Diagnostic value of magnetic resonance imaging and planimetric measurement of optic disc size in confirming optic nerve hypoplasia.
Hellstroem A; Wiklund LM; Svensson E
Journal of AAPOS 1999; 3: 104-108 (IGR: 1-2)


5226 Cup-to-disc ratio: ophthalmoscopy versus automated measurement in a general population: The Rotterdam Study
Wolfs RC; Ramrattan RS; Hofman A; De Jong PT
Ophthalmology 1999; 106: 1597-1601 (IGR: 1-2)



6.30 Other (1088 abstracts found)


84659 Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder
Berchuck SI
Scientific reports 2019; 9: 18113 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Wang M
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Li F
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Sartoretti T
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Zapata MA
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84773 Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients
Lee J
Japanese Journal of Ophthalmology 2020; 64: 68-76 (IGR: 21-1)


84806 Brain morphological alterations of cerebral cortex and subcortical nuclei in high-tension glaucoma brain and its associations with intraocular pressure
Wang Y
Neuroradiology 2020; 62: 495-502 (IGR: 21-1)


84659 Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder
Berchuck SI
Scientific reports 2019; 9: 18113 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Guazzaroni M
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Traber GL
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Wu YY
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


85101 Diagnosis of Glaucoma on Retinal Fundus Images Using Deep Learning: Detection of Nerve Fiber Layer Defect and Optic Disc Analysis
Muramatsu C
Adv Exp Med Biol 2020; 1213: 121-132 (IGR: 21-1)


84979 Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and Meta-analysis
Murtagh P
International Journal of Ophthalmology 2020; 13: 149-162 (IGR: 21-1)


85037 Structurally coloured contact lens sensor for point-of-care ophthalmic health monitoring
Wang Y
Journal of materials chemistry. B 2020; 0: (IGR: 21-1)


84271 Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images
Xu BY
American Journal of Ophthalmology 2019; 208: 273-280 (IGR: 21-1)


85016 Ophthalmic diagnosis using deep learning with fundus images - A critical review
Sengupta S
Artificial Intelligence in Medicine 2020; 102: 101758 (IGR: 21-1)


84271 Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images
Chiang M
American Journal of Ophthalmology 2019; 208: 273-280 (IGR: 21-1)


85016 Ophthalmic diagnosis using deep learning with fundus images - A critical review
Singh A
Artificial Intelligence in Medicine 2020; 102: 101758 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Yan L
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Della Volpe-Waizel M
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Stürmer J
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Wang SF
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Ferrari D
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


84979 Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and Meta-analysis
Greene G
International Journal of Ophthalmology 2020; 13: 149-162 (IGR: 21-1)


85037 Structurally coloured contact lens sensor for point-of-care ophthalmic health monitoring
Zhao Q
Journal of materials chemistry. B 2020; 0: (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Shen LQ
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


84659 Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder
Mukherjee S
Scientific reports 2019; 9: 18113 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Royo-Fibla D
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84806 Brain morphological alterations of cerebral cortex and subcortical nuclei in high-tension glaucoma brain and its associations with intraocular pressure
Wang X
Neuroradiology 2020; 62: 495-502 (IGR: 21-1)


84773 Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients
Kim YK
Japanese Journal of Ophthalmology 2020; 64: 68-76 (IGR: 21-1)


84979 Current applications of machine learning in the screening and diagnosis of glaucoma: a systematic review and Meta-analysis
O'Brien C
International Journal of Ophthalmology 2020; 13: 149-162 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Lamacchia F
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


85016 Ophthalmic diagnosis using deep learning with fundus images - A critical review
Leopold HA
Artificial Intelligence in Medicine 2020; 102: 101758 (IGR: 21-1)


84806 Brain morphological alterations of cerebral cortex and subcortical nuclei in high-tension glaucoma brain and its associations with intraocular pressure
Zhou J
Neuroradiology 2020; 62: 495-502 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Font O
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85037 Structurally coloured contact lens sensor for point-of-care ophthalmic health monitoring
Du X
Journal of materials chemistry. B 2020; 0: (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Zhu PW
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Wang Y
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Maloca P
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Sartoretti E
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Pasquale LR
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


84271 Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images
Chaudhary S
American Journal of Ophthalmology 2019; 208: 273-280 (IGR: 21-1)


84773 Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients
Jeoung JW
Japanese Journal of Ophthalmology 2020; 64: 68-76 (IGR: 21-1)


84659 Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder
Medeiros FA
Scientific reports 2019; 9: 18113 (IGR: 21-1)


84806 Brain morphological alterations of cerebral cortex and subcortical nuclei in high-tension glaucoma brain and its associations with intraocular pressure
Qiu J
Neuroradiology 2020; 62: 495-502 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Vela JI
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Najafi A
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Yuan Q
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Salimei F
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Najafi A
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


85016 Ophthalmic diagnosis using deep learning with fundus images - A critical review
Gulati T
Artificial Intelligence in Medicine 2020; 102: 101758 (IGR: 21-1)


84773 Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients
Ha A
Japanese Journal of Ophthalmology 2020; 64: 68-76 (IGR: 21-1)


84271 Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images
Kulkarni S
American Journal of Ophthalmology 2019; 208: 273-280 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Shi J
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Schmidt-Erfurth U
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Boland MV
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Rubin G
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


84806 Brain morphological alterations of cerebral cortex and subcortical nuclei in high-tension glaucoma brain and its associations with intraocular pressure
Yan T
Neuroradiology 2020; 62: 495-502 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Marcantonio I
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Wellik SR
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Shi WQ
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


84271 Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images
Pardeshi AA
American Journal of Ophthalmology 2019; 208: 273-280 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Schwenk Á
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


85016 Ophthalmic diagnosis using deep learning with fundus images - A critical review
Lakshminarayanan V
Artificial Intelligence in Medicine 2020; 102: 101758 (IGR: 21-1)


84773 Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients
Kim YW
Japanese Journal of Ophthalmology 2020; 64: 68-76 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Chen H
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Marsico S
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Lin Q
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Moya-Sánchez EU
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Wyss M
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


84806 Brain morphological alterations of cerebral cortex and subcortical nuclei in high-tension glaucoma brain and its associations with intraocular pressure
Xie Y
Neuroradiology 2020; 62: 495-502 (IGR: 21-1)


84773 Machine learning classifiers-based prediction of normal-tension glaucoma progression in young myopic patients
Park KH
Japanese Journal of Ophthalmology 2020; 64: 68-76 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
De Moraes CG
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Roska B
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Citraro D
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


84271 Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images
Varma R
American Journal of Ophthalmology 2019; 208: 273-280 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Zhang X; Jiang M
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Campagnuolo T
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Sánchez-Pérez A
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Myers JS
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


84806 Brain morphological alterations of cerebral cortex and subcortical nuclei in high-tension glaucoma brain and its associations with intraocular pressure
Li L
Neuroradiology 2020; 62: 495-502 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Li B
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Cordeiro MF
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Binkert C
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Otto T
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Nguyen TD
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Girardi V
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


84806 Brain morphological alterations of cerebral cortex and subcortical nuclei in high-tension glaucoma brain and its associations with intraocular pressure
Lu W
Neuroradiology 2020; 62: 495-502 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Wu Z
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Min YL
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Garcia-Gasulla D
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


84762 Long segment 3D double inversion recovery (DIR) hypersignal on MRI in glaucomatous optic neuropathy
Sartoretti-Schefer S
BMC Ophthalmology 2019; 19: 258 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Zhou Q
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Weleber R
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Zhou K
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Cortés U
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85103 Biomechanical properties of optic nerve and retrobulbar structures with 2D and 3D shear wave elastography in patients affected by glaucoma
Orlacchio A
Clinical imaging 2020; 61: 106-114 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Ritch R
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Lesmes LA
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Ramulu P
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Lesmes LA
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Ayguadé E
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85092 Altered Intrinsic Functional Connectivity of the Primary Visual Cortex in Patients with Neovascular Glaucoma: A Resting-State Functional Magnetic Resonance Imaging Study
Shao Y
Neuropsychiatric disease and treatment 2020; 16: 25-33 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Arleo A
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85149 Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
Labarta J
Clinical Ophthalmology 2020; 14: 419-429 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Wang H; Tichelaar J
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


84930 New Technologies for Outcome Measures in Glaucoma: Review by the European Vision Institute Special Interest Focus Group
Scholl HPN
Ophthalmic Research 2020; 63: 88-96 (IGR: 21-1)


85127 Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma
Li D; Bex PJ; Elze T
Ophthalmology 2020; 127: 731-738 (IGR: 21-1)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Zhang Q
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82099 Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis
Zhou W
Medical and Biological Engineering and Computing 2019; 57: 2055-2067 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Devalla SK
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Tatewaki Y
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Amil P
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82450 The impact of artificial intelligence in the diagnosis and management of glaucoma
Mayro EL
Eye 2020; 34: 1-11 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Rogers TW
Eye 2019; 33: 1791-1797 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Minosse S
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Phasuk S
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82875 Glaucoma Assessment from OCT images using Capsule Network
Gaddipati DJ
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 5581-5584 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Li L
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82826 Hemoglobin Video Imaging Provides Novel In Vivo High-Resolution Imaging and Quantification of Human Aqueous Outflow in Patients with Glaucoma
Khatib TZ
Ophthalmology. Glaucoma 2019; 2: 327-335 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Zhao R
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Phene S
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Pujari A
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82707 Potential Impact of DARC Technology in Neuroprotective Therapies
Pahlitzsch M
Klinische Monatsblńtter fŘr Augenheilkunde 2020; 237: 140-142 (IGR: 20-4)


82453 Fully automated method for glaucoma screening using robust optic nerve head detection and unsupervised segmentation based cup-to-disc ratio computation in retinal fundus images
Mvoulana A
Computerized Medical Imaging and Graphics 2019; 77: 101643 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Hao H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Christopher M
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82109 Variance components for PIMD-2π estimation of the optic nerve head and consequences in clinical measurements of glaucoma
Sandberg Melin C
Acta Ophthalmologica 2020; 98: 190-194 (IGR: 20-4)


81872 Smartphone-based Gonio-Imaging: A Novel Addition to Glaucoma Screening Tools
Kumar N
Journal of Glaucoma 2019; 28: e149-e150 (IGR: 20-4)


82452 Smartphone use in ophthalmology: What is their place in clinical practice?
Hogarty DT
Survey of Ophthalmology 2020; 65: 250-262 (IGR: 20-4)


82390 Fixel-Based Analysis of Visual Pathway White Matter in Primary Open-Angle Glaucoma
Haykal S
Investigative Ophthalmology and Visual Science 2019; 60: 3803-3812 (IGR: 20-4)


82733 Using soft computing techniques to diagnose Glaucoma disease
Al-Akhras M
Journal of infection and public health 2019; 0: (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Hao H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Wang J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Bajwa MN
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Orlando JI
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Liu S
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82612 Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples
Xu YL
Sensors (Basel, Switzerland) 2019; 19: (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Wang X
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Liu H
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82796 Multi-indices quantification of optic nerve head in fundus image via multitask collaborative learning
Zhao R
Medical Image Analysis 2020; 60: 101593 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Raghavendra U
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Minosse S
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Liao W
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Thakoor KA
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Mao Z
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82733 Using soft computing techniques to diagnose Glaucoma disease
Barakat A
Journal of infection and public health 2019; 0: (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Floris R
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Li L
JAMA ophthalmology 2019; 0: (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Selvan H
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82796 Multi-indices quantification of optic nerve head in fundus image via multitask collaborative learning
Li S
Medical Image Analysis 2020; 60: 101593 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Rumpel H
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


81872 Smartphone-based Gonio-Imaging: A Novel Addition to Glaucoma Screening Tools
Francesco B
Journal of Glaucoma 2019; 28: e149-e150 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Malik MI
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Reyes-Manzano CF
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82452 Smartphone use in ophthalmology: What is their place in clinical practice?
Hogarty JP
Survey of Ophthalmology 2020; 65: 250-262 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Zhao Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Tantibundhit C
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Gudigar A
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Mutoh T
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Hong J
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Fu H
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Yan Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82826 Hemoglobin Video Imaging Provides Novel In Vivo High-Resolution Imaging and Quantification of Human Aqueous Outflow in Patients with Glaucoma
Meyer PAR
Ophthalmology. Glaucoma 2019; 2: 327-335 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Li X
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Shu Y
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82450 The impact of artificial intelligence in the diagnosis and management of glaucoma
Wang M
Eye 2020; 34: 1-11 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zou B
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82612 Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples
Lu S
Sensors (Basel, Switzerland) 2019; 19: (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Bowd C
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82453 Fully automated method for glaucoma screening using robust optic nerve head detection and unsupervised segmentation based cup-to-disc ratio computation in retinal fundus images
Kachouri R
Computerized Medical Imaging and Graphics 2019; 77: 101643 (IGR: 20-4)


82099 Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis
Yi Y
Medical and Biological Engineering and Computing 2019; 57: 2055-2067 (IGR: 20-4)


82109 Variance components for PIMD-2π estimation of the optic nerve head and consequences in clinical measurements of glaucoma
Yu Z
Acta Ophthalmologica 2020; 98: 190-194 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Dunn RC
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82875 Glaucoma Assessment from OCT images using Capsule Network
Desai A
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 5581-5584 (IGR: 20-4)


82390 Fixel-Based Analysis of Visual Pathway White Matter in Primary Open-Angle Glaucoma
Curcic-Blake B
Investigative Ophthalmology and Visual Science 2019; 60: 3803-3812 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Jaccard N
Eye 2019; 33: 1791-1797 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Xu M
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Liang Z
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Miki A
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Chen X
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82453 Fully automated method for glaucoma screening using robust optic nerve head detection and unsupervised segmentation based cup-to-disc ratio computation in retinal fundus images
Akil M
Computerized Medical Imaging and Graphics 2019; 77: 101643 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Fu H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Belghith A
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82826 Hemoglobin Video Imaging Provides Novel In Vivo High-Resolution Imaging and Quantification of Human Aqueous Outflow in Patients with Glaucoma
Lusthaus J
Ophthalmology. Glaucoma 2019; 2: 327-335 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Tsamis E
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Lu X
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Wormstone IM
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Li X
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Bhandary SV
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82109 Variance components for PIMD-2π estimation of the optic nerve head and consequences in clinical measurements of glaucoma
Söderberg PG
Acta Ophthalmologica 2020; 98: 190-194 (IGR: 20-4)


82733 Using soft computing techniques to diagnose Glaucoma disease
Alawairdhi M
Journal of infection and public health 2019; 0: (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Siddiqui SA
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82450 The impact of artificial intelligence in the diagnosis and management of glaucoma
Elze T
Eye 2020; 34: 1-11 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Tsamis E
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82390 Fixel-Based Analysis of Visual Pathway White Matter in Primary Open-Angle Glaucoma
Jansonius NM
Investigative Ophthalmology and Visual Science 2019; 60: 3803-3812 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Mei S
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82612 Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples
Li HX
Sensors (Basel, Switzerland) 2019; 19: (IGR: 20-4)


82875 Glaucoma Assessment from OCT images using Capsule Network
Sivaswamy J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 5581-5584 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zhao R
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82099 Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis
Bao J
Medical and Biological Engineering and Computing 2019; 57: 2055-2067 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Baskaran M
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Omodaka K
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Tsamis E
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Carbonaro F
Eye 2019; 33: 1791-1797 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Liu H
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Hammel N
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Pham TH
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


81872 Smartphone-based Gonio-Imaging: A Novel Addition to Glaucoma Screening Tools
Sharma A
Journal of Glaucoma 2019; 28: e149-e150 (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Asif MI
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Guzmán-Vargas L
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82452 Smartphone use in ophthalmology: What is their place in clinical practice?
Hewitt AW
Survey of Ophthalmology 2020; 65: 250-262 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Nucci C
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Barbosa Breda J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Poopresert P
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Xu Y
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Xiyao L
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Jia X
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Li Y
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Liu Y
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Yaemsuk A
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Xiong C
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Rao TN
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82875 Glaucoma Assessment from OCT images using Capsule Network
Vermeer KA
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 5581-5584 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Chen Y
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82390 Fixel-Based Analysis of Visual Pathway White Matter in Primary Open-Angle Glaucoma
Cornelissen FW
Investigative Ophthalmology and Visual Science 2019; 60: 3803-3812 (IGR: 20-4)


82612 Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples
Li RR
Sensors (Basel, Switzerland) 2019; 19: (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Toschi N
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Shang Q
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Van Keer K
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Sajda P
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82099 Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis
Wang W
Medical and Biological Engineering and Computing 2019; 57: 2055-2067 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Thyreau B
Scientific reports 2019; 9: 15148 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Tun TA
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Dengel A
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Dong Y
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Goldbaum MH
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Boote C
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Zhao W
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Gupta B
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Zailiang C
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82826 Hemoglobin Video Imaging Provides Novel In Vivo High-Resolution Imaging and Quantification of Human Aqueous Outflow in Patients with Glaucoma
Manyakin I
Ophthalmology. Glaucoma 2019; 2: 327-335 (IGR: 20-4)


82733 Using soft computing techniques to diagnose Glaucoma disease
Habib M
Journal of infection and public health 2019; 0: (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Shang Q
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Qiao C
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82450 The impact of artificial intelligence in the diagnosis and management of glaucoma
Pasquale LR
Eye 2020; 34: 1-11 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Lemij HG
Eye 2019; 33: 1791-1797 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Sendiña-Nadal I
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Strouthidis N
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Min H
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Guo F
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Strouthidis NG
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Bathula DR
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82826 Hemoglobin Video Imaging Provides Novel In Vivo High-Resolution Imaging and Quantification of Human Aqueous Outflow in Patients with Glaucoma
Mushtaq Y
Ophthalmology. Glaucoma 2019; 2: 327-335 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Vermeer KA
Eye 2019; 33: 1791-1797 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Strouthidis N
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Matsudaira I
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Masoller C
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Wang X
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Suvannachart P
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Li P
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Ciaccio EJ
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Maruyama K
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Shafait F
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Garaci F
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Lin Z
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
He Z
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82866 Enhancing the Accuracy of Glaucoma Detection from OCT Probability Maps using Convolutional Neural Networks
Hood DC
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2036-2040 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Li F
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Weinreb RN
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Zhang C
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Krause J
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


81895 Smartphone-aided Quantification of Iridocorneal Angle
Dada T
Journal of Glaucoma 2019; 28: e153-e155 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Perera SA
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Zhang X
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Liu P
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Kitade N
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zhou M
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Diaz-Pinto A
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Tan M
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Zhou Y
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Martucci A
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82108 A Two Layer Sparse Autoencoder for Glaucoma Identification with Fundus Images
Acharya UR
Journal of Medical Systems 2019; 43: 299 (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Thiery AH
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Itthipanichpong R
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Reus NJ
Eye 2019; 33: 1791-1797 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Jiang L
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Diaz-Pinto A
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82826 Hemoglobin Video Imaging Provides Novel In Vivo High-Resolution Imaging and Quantification of Human Aqueous Outflow in Patients with Glaucoma
Martin KR
Ophthalmology. Glaucoma 2019; 2: 327-335 (IGR: 20-4)


82209 Direct Cup-to-Disc Ratio Estimation for Glaucoma Screening via Semi-supervised Learning
Li S
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Kawasaki R
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Fazio MA
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Pang Y
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Furukawa H
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82023 Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Neumeier W; Ahmed S
BMC Medical Informatics and Decision Making 2019; 19: 136 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Usui S
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82865 Conditional Adversarial Transfer for Glaucoma Diagnosis
Liu J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 2032-2035 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Li S
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82682 Glaucoma management in the era of artificial intelligence
Girard MJA
British Journal of Ophthalmology 2020; 104: 301-311 (IGR: 20-4)


81946 Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study
Trikha S
Eye 2019; 33: 1791-1797 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Wang Z
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Girkin CA
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Lanzafame S
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Liu Y
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


82862 Anterior Chamber Angles Classification in Anterior Segment OCT Images via Multi-Scale Regions Convolutional Neural Networks
Liu J
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 849-852 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Nongpiur ME
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Lanzafame S
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Chansangpetch S
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Schaekermann M
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Ye W
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Yamada K
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Fang R
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Sayres R
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82648 Joint optic disc and cup segmentation using semi-supervised conditional GANs
Zhang H
Computers in Biology and Medicine 2019; 115: 103485 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Fan X
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Liebmann JM
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Heng PA
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Matsushita K
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Yang L
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Di Giuliano F
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Manassakorn A
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Lim WEH
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Kunitoki K
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Heng PA
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Wang H
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Di Giuliano F
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Tantisevi V
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


81972 A Large-Scale Database and a CNN Model for Attention-Based Glaucoma Detection
Wang N
IEEE Transactions on Medical Imaging 2020; 39: 413-424 (IGR: 20-4)


82788 Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Zangwill LM
Ophthalmology 2020; 127: 346-356 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Aung T
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Wu DJ
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Mou D
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Nishida K
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Zeng X
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Picchi E
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Kim J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Picchi E
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Kawashima R; Nakazawa T
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Lee J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Milea D
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82864 Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning
Rojanapongpun P
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 904-907 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Bora A
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Pang R
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Cesareo M
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82491 Resting-state functional magnetic resonance study of primary open-angle glaucoma based on voxelwise brain network degree centrality
Zhang X
Neuroscience Letters 2019; 712: 134500 (IGR: 20-4)


82834 Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans
Chan K
Biomedical optics express 2019; 10: 5832-5851 (IGR: 20-4)


82683 Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images
Taki Y
Scientific reports 2019; 9: 15148 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Mancino R
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Yang D
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Semturs C
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


81723 Optic Nerve Tortuosity and Globe Proptosis in Normal and Glaucoma Subjects
Girard MJA
Journal of Glaucoma 2019; 28: 691-696 (IGR: 20-4)


82868 Disruption of brain network organization in primary open angle glaucoma
Guerrisi M; Guerrisi M
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4338-4341 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Misra A
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Li X
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Jiang L
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Liu P
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Chen Y
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Huang AE
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Lu S
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Spitze A
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Hu M
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Murugesan B
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Medeiros FA
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Xu Y
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Naranjo V
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Maa AY
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Naranjo V
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Kang H; Ji X
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Phaye SSR
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Gandhi M; Corrado GS
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Chang R
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Shankaranarayana SM
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Tham C
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Sikka A
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Peng L
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Cheung C
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Son J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82499 Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Webster DR
Ophthalmology 2019; 126: 1627-1639 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Ting DSW
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
van den Hengel A
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Wong TY
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Wang S; Wu J
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Wang Z
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Wu Z
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Weinreb RN
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Xu G
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


82400 Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs
Xu M; Wang N
JAMA ophthalmology 2019; 0: (IGR: 20-4)


82647 REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Xu Y; Yin
Medical Image Analysis 2020; 59: 101570 (IGR: 20-4)


80738 Decreased orbital fat and enophthalmos due to bimatoprost: Quantitative analysis using magnetic resonance imaging
Higashiyama T
PLoS ONE 2019; 14: e0214065 (IGR: 20-3)


81194 Characterization of the ocular surface temperature dynamics in glaucoma subjects using long-wave infrared thermal imaging
García-Porta N
Journal of the Optical Society of America. A, Optics, Image Science, and Vision 2019; 36: 1015-1021 (IGR: 20-3)


81180 Linking neural and clinical measures of glaucoma with diffusion magnetic resonance imaging (dMRI)
Miller N
PLoS ONE 2019; 14: e0217011 (IGR: 20-3)


81356 Evaluation of optic canal anatomy and symmetry using CT
Zhang X
BMJ open ophthalmology 2019; 4: e000302 (IGR: 20-3)


81451 SPECIFIC CHARACTERISTICS OF OCULAR BIOMETRIC FACTORS IN GLAUCOMATOUS PATIENTS WITH PSEUDOEXFOLIATIVE SYNDROME AS MEASURED BY OPTICAL LOW-COHERENCE REFLECTOMETRY
Janjetović Ž
Acta Clinica Croatica 2019; 58: 87-94 (IGR: 20-3)


80502 Diagnostic utility of central damage determination in glaucoma by magnetic resonance imaging: An observational study
Li M
Experimental and therapeutic medicine 2019; 17: 1891-1895 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Wang Y
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Al-Aswad LA
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


81390 Postural changes in patients with visual deficits
Serin-Brackman V
Journal Franšais d'Ophtalmologie 2019; 42: 1078-1084 (IGR: 20-3)


80654 Detecting autonomic dysfunction in patients with glaucoma using dynamic pupillometry
Park HL
Medicine 2019; 98: e14658 (IGR: 20-3)


81173 Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state
Chen L
Quantitative imaging in medicine and surgery 2019; 9: 603-614 (IGR: 20-3)


81404 Eye Movements of Drivers with Glaucoma on a Visual Recognition Slide Test
Lee SS
Optometry and Vision Science 2019; 96: 484-491 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Qu X
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


81356 Evaluation of optic canal anatomy and symmetry using CT
Lee Y
BMJ open ophthalmology 2019; 4: e000302 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Wang Q
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


80502 Diagnostic utility of central damage determination in glaucoma by magnetic resonance imaging: An observational study
Ke M
Experimental and therapeutic medicine 2019; 17: 1891-1895 (IGR: 20-3)


81404 Eye Movements of Drivers with Glaucoma on a Visual Recognition Slide Test
Black AA
Optometry and Vision Science 2019; 96: 484-491 (IGR: 20-3)


81194 Characterization of the ocular surface temperature dynamics in glaucoma subjects using long-wave infrared thermal imaging
Gantes-Nuñez FJ
Journal of the Optical Society of America. A, Optics, Image Science, and Vision 2019; 36: 1015-1021 (IGR: 20-3)


81173 Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state
Li S
Quantitative imaging in medicine and surgery 2019; 9: 603-614 (IGR: 20-3)


80738 Decreased orbital fat and enophthalmos due to bimatoprost: Quantitative analysis using magnetic resonance imaging
Minamikawa T
PLoS ONE 2019; 14: e0214065 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Kapoor R
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


81180 Linking neural and clinical measures of glaucoma with diffusion magnetic resonance imaging (dMRI)
Liu Y
PLoS ONE 2019; 14: e0217011 (IGR: 20-3)


81390 Postural changes in patients with visual deficits
Pezet Poux J
Journal Franšais d'Ophtalmologie 2019; 42: 1078-1084 (IGR: 20-3)


81451 SPECIFIC CHARACTERISTICS OF OCULAR BIOMETRIC FACTORS IN GLAUCOMATOUS PATIENTS WITH PSEUDOEXFOLIATIVE SYNDROME AS MEASURED BY OPTICAL LOW-COHERENCE REFLECTOMETRY
Bušić M
Acta Clinica Croatica 2019; 58: 87-94 (IGR: 20-3)


80654 Detecting autonomic dysfunction in patients with glaucoma using dynamic pupillometry
Jung SH
Medicine 2019; 98: e14658 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Kapoor R
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Lu W
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81404 Eye Movements of Drivers with Glaucoma on a Visual Recognition Slide Test
Wood JM
Optometry and Vision Science 2019; 96: 484-491 (IGR: 20-3)


81173 Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state
Cai F
Quantitative imaging in medicine and surgery 2019; 9: 603-614 (IGR: 20-3)


81390 Postural changes in patients with visual deficits
Quintyn JC
Journal Franšais d'Ophtalmologie 2019; 42: 1078-1084 (IGR: 20-3)


81451 SPECIFIC CHARACTERISTICS OF OCULAR BIOMETRIC FACTORS IN GLAUCOMATOUS PATIENTS WITH PSEUDOEXFOLIATIVE SYNDROME AS MEASURED BY OPTICAL LOW-COHERENCE REFLECTOMETRY
Bosnar D
Acta Clinica Croatica 2019; 58: 87-94 (IGR: 20-3)


80654 Detecting autonomic dysfunction in patients with glaucoma using dynamic pupillometry
Park SH
Medicine 2019; 98: e14658 (IGR: 20-3)


81356 Evaluation of optic canal anatomy and symmetry using CT
Olson D
BMJ open ophthalmology 2019; 4: e000302 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Chen W
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


81180 Linking neural and clinical measures of glaucoma with diffusion magnetic resonance imaging (dMRI)
Krivochenitser R
PLoS ONE 2019; 14: e0217011 (IGR: 20-3)


80502 Diagnostic utility of central damage determination in glaucoma by magnetic resonance imaging: An observational study
Song Y
Experimental and therapeutic medicine 2019; 17: 1891-1895 (IGR: 20-3)


80738 Decreased orbital fat and enophthalmos due to bimatoprost: Quantitative analysis using magnetic resonance imaging
Kakinoki M
PLoS ONE 2019; 14: e0214065 (IGR: 20-3)


81194 Characterization of the ocular surface temperature dynamics in glaucoma subjects using long-wave infrared thermal imaging
Tabernero J
Journal of the Optical Society of America. A, Optics, Image Science, and Vision 2019; 36: 1015-1021 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Chu CK
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Yan T
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81173 Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state
Wu L
Quantitative imaging in medicine and surgery 2019; 9: 603-614 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Walters S
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


80738 Decreased orbital fat and enophthalmos due to bimatoprost: Quantitative analysis using magnetic resonance imaging
Sawada O
PLoS ONE 2019; 14: e0214065 (IGR: 20-3)


81451 SPECIFIC CHARACTERISTICS OF OCULAR BIOMETRIC FACTORS IN GLAUCOMATOUS PATIENTS WITH PSEUDOEXFOLIATIVE SYNDROME AS MEASURED BY OPTICAL LOW-COHERENCE REFLECTOMETRY
Barać J
Acta Clinica Croatica 2019; 58: 87-94 (IGR: 20-3)


80654 Detecting autonomic dysfunction in patients with glaucoma using dynamic pupillometry
Park CK
Medicine 2019; 98: e14658 (IGR: 20-3)


81194 Characterization of the ocular surface temperature dynamics in glaucoma subjects using long-wave infrared thermal imaging
Pardhan S
Journal of the Optical Society of America. A, Optics, Image Science, and Vision 2019; 36: 1015-1021 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Zhou J
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81356 Evaluation of optic canal anatomy and symmetry using CT
Fleischman D
BMJ open ophthalmology 2019; 4: e000302 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Li T
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


81180 Linking neural and clinical measures of glaucoma with diffusion magnetic resonance imaging (dMRI)
Rokers B
PLoS ONE 2019; 14: e0217011 (IGR: 20-3)


80502 Diagnostic utility of central damage determination in glaucoma by magnetic resonance imaging: An observational study
Mu K; Zhang H
Experimental and therapeutic medicine 2019; 17: 1891-1895 (IGR: 20-3)


81173 Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state
Gong H
Quantitative imaging in medicine and surgery 2019; 9: 603-614 (IGR: 20-3)


80738 Decreased orbital fat and enophthalmos due to bimatoprost: Quantitative analysis using magnetic resonance imaging
Ohji M
PLoS ONE 2019; 14: e0214065 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Guo J
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Gong D
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Xie Y
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81451 SPECIFIC CHARACTERISTICS OF OCULAR BIOMETRIC FACTORS IN GLAUCOMATOUS PATIENTS WITH PSEUDOEXFOLIATIVE SYNDROME AS MEASURED BY OPTICAL LOW-COHERENCE REFLECTOMETRY
Genda I
Acta Clinica Croatica 2019; 58: 87-94 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Wang H
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Garg A
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


80502 Diagnostic utility of central damage determination in glaucoma by magnetic resonance imaging: An observational study
Chen Z
Experimental and therapeutic medicine 2019; 17: 1891-1895 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Yuan J
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81173 Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state
Pei C
Quantitative imaging in medicine and surgery 2019; 9: 603-614 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Zhang X
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Gopal K
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


81173 Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state
Zhou F
Quantitative imaging in medicine and surgery 2019; 9: 603-614 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Gopal K
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Liu G
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Wang Y
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


81173 Altered functional connectivity density in primary angle-closure glaucoma patients at resting-state
Zeng X
Quantitative imaging in medicine and surgery 2019; 9: 603-614 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Teng Y
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Patel V
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Han W
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Sameer T
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Wang N
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Chen D
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81014 Combined machine learning and diffusion tensor imaging reveals altered anatomic fiber connectivity of the brain in primary open-angle glaucoma
Xian J
Brain Research 2019; 1718: 83-90 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
Rogers TW; Nicolas J
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


80522 Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients
Qiu J
Acta Ophthalmologica 2019; 97: e341-e348 (IGR: 20-3)


81330 Evaluation of a Deep Learning System for Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs
De Moraes CG; Moazami G
Journal of Glaucoma 2019; 28: 1029-1034 (IGR: 20-3)


79401 Vection Responses in Patients With Early Glaucoma
Brin TA
Journal of Glaucoma 2019; 28: 68-74 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Shigueoka LS
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79856 Subcortical visual pathway may be a new way for early diagnosis of glaucoma
Sun Y
Medical Hypotheses 2019; 123: 47-49 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Wang M
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79338 A deep learning approach to automatic detection of early glaucoma from visual fields
Kucur ŞS
PLoS ONE 2018; 13: e0206081 (IGR: 20-2)


79898 Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation
Lee J
Journal of Glaucoma 2019; 28: 258-264 (IGR: 20-2)


79852 Frequency-dependent neural activity in primary angle-closure glaucoma
Jiang F
Neuropsychiatric disease and treatment 2019; 15: 271-282 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Vasconcellos JPC
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79898 Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation
Kim Y
Journal of Glaucoma 2019; 28: 258-264 (IGR: 20-2)


79338 A deep learning approach to automatic detection of early glaucoma from visual fields
Holló G
PLoS ONE 2018; 13: e0206081 (IGR: 20-2)


79852 Frequency-dependent neural activity in primary angle-closure glaucoma
Yu C
Neuropsychiatric disease and treatment 2019; 15: 271-282 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Shen LQ
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79856 Subcortical visual pathway may be a new way for early diagnosis of glaucoma
Huang W
Medical Hypotheses 2019; 123: 47-49 (IGR: 20-2)


79401 Vection Responses in Patients With Early Glaucoma
Tarita-Nistor L
Journal of Glaucoma 2019; 28: 68-74 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Pasquale LR
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Schimiti RB
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79898 Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation
Kim JH
Journal of Glaucoma 2019; 28: 258-264 (IGR: 20-2)


79852 Frequency-dependent neural activity in primary angle-closure glaucoma
Zuo MJ
Neuropsychiatric disease and treatment 2019; 15: 271-282 (IGR: 20-2)


79401 Vection Responses in Patients With Early Glaucoma
González EG
Journal of Glaucoma 2019; 28: 68-74 (IGR: 20-2)


79856 Subcortical visual pathway may be a new way for early diagnosis of glaucoma
Li F
Medical Hypotheses 2019; 123: 47-49 (IGR: 20-2)


79338 A deep learning approach to automatic detection of early glaucoma from visual fields
Sznitman R
PLoS ONE 2018; 13: e0206081 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Petrakos P
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79401 Vection Responses in Patients With Early Glaucoma
Trope GE
Journal of Glaucoma 2019; 28: 68-74 (IGR: 20-2)


79852 Frequency-dependent neural activity in primary angle-closure glaucoma
Zhang C
Neuropsychiatric disease and treatment 2019; 15: 271-282 (IGR: 20-2)


79898 Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation
Park KH
Journal of Glaucoma 2019; 28: 258-264 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Reis ASC
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79856 Subcortical visual pathway may be a new way for early diagnosis of glaucoma
Li H
Medical Hypotheses 2019; 123: 47-49 (IGR: 20-2)


79852 Frequency-dependent neural activity in primary angle-closure glaucoma
Wang Y
Neuropsychiatric disease and treatment 2019; 15: 271-282 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Formica S
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79856 Subcortical visual pathway may be a new way for early diagnosis of glaucoma
Wang L
Medical Hypotheses 2019; 123: 47-49 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Oliveira GO
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79401 Vection Responses in Patients With Early Glaucoma
Steinbach MJ
Journal of Glaucoma 2019; 28: 68-74 (IGR: 20-2)


79856 Subcortical visual pathway may be a new way for early diagnosis of glaucoma
Huang Y
Medical Hypotheses 2019; 123: 47-49 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Gomi ES
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79852 Frequency-dependent neural activity in primary angle-closure glaucoma
Zhou FQ
Neuropsychiatric disease and treatment 2019; 15: 271-282 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Boland MV
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79856 Subcortical visual pathway may be a new way for early diagnosis of glaucoma
Zhang X
Medical Hypotheses 2019; 123: 47-49 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Wellik SR
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Vianna JAR
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79852 Frequency-dependent neural activity in primary angle-closure glaucoma
Zeng XJ
Neuropsychiatric disease and treatment 2019; 15: 271-282 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
De Moraes CG
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Lisboa RDDR; Medeiros FA
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Myers JS; Saeedi O
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


79815 Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
Costa VP
PLoS ONE 2018; 13: e0207784 (IGR: 20-2)


79883 An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis
Wang H; Baniasadi N; Li D; Tichelaar J; Bex PJ; Elze T
Investigative Ophthalmology and Visual Science 2019; 60: 365-375 (IGR: 20-2)


78583 Reduced Cerebral Blood Flow in the Visual Cortex and Its Correlation With Glaucomatous Structural Damage to the Retina in Patients With Mild to Moderate Primary Open-angle Glaucoma
Wang Q
Journal of Glaucoma 2018; 27: 816-822 (IGR: 20-1)


78943 Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study
Daga FB
Investigative Ophthalmology and Visual Science 2018; 59: 4471-4476 (IGR: 20-1)


79097 Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension
Song XY
Frontiers in human neuroscience 2018; 12: 426 (IGR: 20-1)


78527 Evidence for alterations in fixational eye movements in glaucoma
Montesano G
BMC Ophthalmology 2018; 18: 191 (IGR: 20-1)


79262 Magnetic Resonance Spectroscopy Features of the Visual Pathways in Patients with Glaucoma
Aksoy DÖ
Clinical neuroradiology 2019; 29: 615-621 (IGR: 20-1)


78820 Noninvasive intracranial pressure assessment using otoacoustic emissions: An application in glaucoma
Loiselle AR
PLoS ONE 2018; 13: e0204939 (IGR: 20-1)


79298 Inner Retinal Changes in Primary Open-Angle Glaucoma Revealed Through Adaptive Optics-Optical Coherence Tomography
Wells-Gray EM; Choi SS
Journal of Glaucoma 2018; 27: 1025-1028 (IGR: 20-1)


78820 Noninvasive intracranial pressure assessment using otoacoustic emissions: An application in glaucoma
de Kleine E
PLoS ONE 2018; 13: e0204939 (IGR: 20-1)


79097 Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension
Puyang Z
Frontiers in human neuroscience 2018; 12: 426 (IGR: 20-1)


78527 Evidence for alterations in fixational eye movements in glaucoma
Crabb DP
BMC Ophthalmology 2018; 18: 191 (IGR: 20-1)


78583 Reduced Cerebral Blood Flow in the Visual Cortex and Its Correlation With Glaucomatous Structural Damage to the Retina in Patients With Mild to Moderate Primary Open-angle Glaucoma
Chen W
Journal of Glaucoma 2018; 27: 816-822 (IGR: 20-1)


79262 Magnetic Resonance Spectroscopy Features of the Visual Pathways in Patients with Glaucoma
Umurhan Akkan JC
Clinical neuroradiology 2019; 29: 615-621 (IGR: 20-1)


78943 Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study
Ogata NG
Investigative Ophthalmology and Visual Science 2018; 59: 4471-4476 (IGR: 20-1)


78527 Evidence for alterations in fixational eye movements in glaucoma
Jones PR
BMC Ophthalmology 2018; 18: 191 (IGR: 20-1)


79298 Inner Retinal Changes in Primary Open-Angle Glaucoma Revealed Through Adaptive Optics-Optical Coherence Tomography
Slabaugh M
Journal of Glaucoma 2018; 27: 1025-1028 (IGR: 20-1)


78943 Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study
Medeiros FA
Investigative Ophthalmology and Visual Science 2018; 59: 4471-4476 (IGR: 20-1)


78820 Noninvasive intracranial pressure assessment using otoacoustic emissions: An application in glaucoma
van Dijk P
PLoS ONE 2018; 13: e0204939 (IGR: 20-1)


79097 Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension
Chen AH
Frontiers in human neuroscience 2018; 12: 426 (IGR: 20-1)


79262 Magnetic Resonance Spectroscopy Features of the Visual Pathways in Patients with Glaucoma
Alkan A
Clinical neuroradiology 2019; 29: 615-621 (IGR: 20-1)


78583 Reduced Cerebral Blood Flow in the Visual Cortex and Its Correlation With Glaucomatous Structural Damage to the Retina in Patients With Mild to Moderate Primary Open-angle Glaucoma
Qu X
Journal of Glaucoma 2018; 27: 816-822 (IGR: 20-1)


79262 Magnetic Resonance Spectroscopy Features of the Visual Pathways in Patients with Glaucoma
Aralaşmak A
Clinical neuroradiology 2019; 29: 615-621 (IGR: 20-1)


78527 Evidence for alterations in fixational eye movements in glaucoma
Fogagnolo P
BMC Ophthalmology 2018; 18: 191 (IGR: 20-1)


78583 Reduced Cerebral Blood Flow in the Visual Cortex and Its Correlation With Glaucomatous Structural Damage to the Retina in Patients With Mild to Moderate Primary Open-angle Glaucoma
Wang H
Journal of Glaucoma 2018; 27: 816-822 (IGR: 20-1)


78820 Noninvasive intracranial pressure assessment using otoacoustic emissions: An application in glaucoma
Jansonius NM
PLoS ONE 2018; 13: e0204939 (IGR: 20-1)


79298 Inner Retinal Changes in Primary Open-Angle Glaucoma Revealed Through Adaptive Optics-Optical Coherence Tomography
Weber P
Journal of Glaucoma 2018; 27: 1025-1028 (IGR: 20-1)


78943 Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study
Moran R
Investigative Ophthalmology and Visual Science 2018; 59: 4471-4476 (IGR: 20-1)


79097 Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension
Zhao J
Frontiers in human neuroscience 2018; 12: 426 (IGR: 20-1)


78583 Reduced Cerebral Blood Flow in the Visual Cortex and Its Correlation With Glaucomatous Structural Damage to the Retina in Patients With Mild to Moderate Primary Open-angle Glaucoma
Wang Y
Journal of Glaucoma 2018; 27: 816-822 (IGR: 20-1)


78943 Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study
Morris J
Investigative Ophthalmology and Visual Science 2018; 59: 4471-4476 (IGR: 20-1)


79298 Inner Retinal Changes in Primary Open-Angle Glaucoma Revealed Through Adaptive Optics-Optical Coherence Tomography
Doble N
Journal of Glaucoma 2018; 27: 1025-1028 (IGR: 20-1)


79097 Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension
Li XJ
Frontiers in human neuroscience 2018; 12: 426 (IGR: 20-1)


79262 Magnetic Resonance Spectroscopy Features of the Visual Pathways in Patients with Glaucoma
Otçu Temur H
Clinical neuroradiology 2019; 29: 615-621 (IGR: 20-1)


78527 Evidence for alterations in fixational eye movements in glaucoma
Digiuni M
BMC Ophthalmology 2018; 18: 191 (IGR: 20-1)


79262 Magnetic Resonance Spectroscopy Features of the Visual Pathways in Patients with Glaucoma
Yurtsever İ
Clinical neuroradiology 2019; 29: 615-621 (IGR: 20-1)


78527 Evidence for alterations in fixational eye movements in glaucoma
Rossetti LM
BMC Ophthalmology 2018; 18: 191 (IGR: 20-1)


79097 Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension
Chen YY
Frontiers in human neuroscience 2018; 12: 426 (IGR: 20-1)


78583 Reduced Cerebral Blood Flow in the Visual Cortex and Its Correlation With Glaucomatous Structural Damage to the Retina in Patients With Mild to Moderate Primary Open-angle Glaucoma
Zhang X
Journal of Glaucoma 2018; 27: 816-822 (IGR: 20-1)


78943 Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study
Zangwill LM
Investigative Ophthalmology and Visual Science 2018; 59: 4471-4476 (IGR: 20-1)


78583 Reduced Cerebral Blood Flow in the Visual Cortex and Its Correlation With Glaucomatous Structural Damage to the Retina in Patients With Mild to Moderate Primary Open-angle Glaucoma
Li T
Journal of Glaucoma 2018; 27: 816-822 (IGR: 20-1)


78943 Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study
Weinreb RN
Investigative Ophthalmology and Visual Science 2018; 59: 4471-4476 (IGR: 20-1)


79097 Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension
Tang WJ
Frontiers in human neuroscience 2018; 12: 426 (IGR: 20-1)


78943 Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study
Nolan JM
Investigative Ophthalmology and Visual Science 2018; 59: 4471-4476 (IGR: 20-1)


79097 Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension
Zhang YY
Frontiers in human neuroscience 2018; 12: 426 (IGR: 20-1)


78583 Reduced Cerebral Blood Flow in the Visual Cortex and Its Correlation With Glaucomatous Structural Damage to the Retina in Patients With Mild to Moderate Primary Open-angle Glaucoma
Wang N; Xian J
Journal of Glaucoma 2018; 27: 816-822 (IGR: 20-1)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Fukuda M
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


78075 Undilated versus dilated monoscopic smartphone-based fundus photography for optic nerve head evaluation
Wintergerst MWM
Scientific reports 2018; 8: 10228 (IGR: 19-4)


77956 Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning
Yousefi S
American Journal of Ophthalmology 2018; 193: 71-79 (IGR: 19-4)


78038 Quantification of blood flow in the superior ophthalmic vein using phase contrast magnetic resonance imaging
Promelle V
Experimental Eye Research 2018; 176: 40-45 (IGR: 19-4)


78018 Diacaustic examination of the iridocorneal angle : Video article
Zhuravlyov A
Ophthalmologe 2018; 115: 606-612 (IGR: 19-4)


77687 Noninvasive Detection of Mitochondrial Dysfunction in Ocular Hypertension and Primary Open-angle Glaucoma
Geyman LS
Journal of Glaucoma 2018; 27: 592-599 (IGR: 19-4)


78250 Lacrimal Gland Changes on Orbital Imaging after Glaucoma Drainage Implant Surgery
Jacobs SM
Journal of ophthalmic & vision research 2018; 13: 219-223 (IGR: 19-4)


78207 Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma
Martin KR
American Journal of Ophthalmology 2018; 194: 46-53 (IGR: 19-4)


77893 Investigation of lateral geniculate nucleus volume and diffusion tensor imaging in patients with normal tension glaucoma using 7 tesla magnetic resonance imaging
Schmidt MA
PLoS ONE 2018; 13: e0198830 (IGR: 19-4)


77956 Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning
Kiwaki T
American Journal of Ophthalmology 2018; 193: 71-79 (IGR: 19-4)


78207 Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma
Mansouri K
American Journal of Ophthalmology 2018; 194: 46-53 (IGR: 19-4)


78250 Lacrimal Gland Changes on Orbital Imaging after Glaucoma Drainage Implant Surgery
Mudumbai RC
Journal of ophthalmic & vision research 2018; 13: 219-223 (IGR: 19-4)


77687 Noninvasive Detection of Mitochondrial Dysfunction in Ocular Hypertension and Primary Open-angle Glaucoma
Suwan Y
Journal of Glaucoma 2018; 27: 592-599 (IGR: 19-4)


77893 Investigation of lateral geniculate nucleus volume and diffusion tensor imaging in patients with normal tension glaucoma using 7 tesla magnetic resonance imaging
Knott M
PLoS ONE 2018; 13: e0198830 (IGR: 19-4)


78075 Undilated versus dilated monoscopic smartphone-based fundus photography for optic nerve head evaluation
Brinkmann CK
Scientific reports 2018; 8: 10228 (IGR: 19-4)


78038 Quantification of blood flow in the superior ophthalmic vein using phase contrast magnetic resonance imaging
Bouzerar R
Experimental Eye Research 2018; 176: 40-45 (IGR: 19-4)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Omodaka K
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


78250 Lacrimal Gland Changes on Orbital Imaging after Glaucoma Drainage Implant Surgery
Amadi AJ
Journal of ophthalmic & vision research 2018; 13: 219-223 (IGR: 19-4)


77687 Noninvasive Detection of Mitochondrial Dysfunction in Ocular Hypertension and Primary Open-angle Glaucoma
Garg R
Journal of Glaucoma 2018; 27: 592-599 (IGR: 19-4)


78075 Undilated versus dilated monoscopic smartphone-based fundus photography for optic nerve head evaluation
Holz FG
Scientific reports 2018; 8: 10228 (IGR: 19-4)


78038 Quantification of blood flow in the superior ophthalmic vein using phase contrast magnetic resonance imaging
Milazzo S
Experimental Eye Research 2018; 176: 40-45 (IGR: 19-4)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Tatewaki Y
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


78207 Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma
Weinreb RN
American Journal of Ophthalmology 2018; 194: 46-53 (IGR: 19-4)


77956 Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning
Zheng Y
American Journal of Ophthalmology 2018; 193: 71-79 (IGR: 19-4)


77893 Investigation of lateral geniculate nucleus volume and diffusion tensor imaging in patients with normal tension glaucoma using 7 tesla magnetic resonance imaging
Heidemann R
PLoS ONE 2018; 13: e0198830 (IGR: 19-4)


78038 Quantification of blood flow in the superior ophthalmic vein using phase contrast magnetic resonance imaging
Balédent O
Experimental Eye Research 2018; 176: 40-45 (IGR: 19-4)


77956 Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning
Sugiura H
American Journal of Ophthalmology 2018; 193: 71-79 (IGR: 19-4)


77687 Noninvasive Detection of Mitochondrial Dysfunction in Ocular Hypertension and Primary Open-angle Glaucoma
Field MG
Journal of Glaucoma 2018; 27: 592-599 (IGR: 19-4)


78207 Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma
Wasilewicz R
American Journal of Ophthalmology 2018; 194: 46-53 (IGR: 19-4)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Himori N
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


77893 Investigation of lateral geniculate nucleus volume and diffusion tensor imaging in patients with normal tension glaucoma using 7 tesla magnetic resonance imaging
Michelson G
PLoS ONE 2018; 13: e0198830 (IGR: 19-4)


78075 Undilated versus dilated monoscopic smartphone-based fundus photography for optic nerve head evaluation
Finger RP
Scientific reports 2018; 8: 10228 (IGR: 19-4)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Matsudaira I
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


77893 Investigation of lateral geniculate nucleus volume and diffusion tensor imaging in patients with normal tension glaucoma using 7 tesla magnetic resonance imaging
Kober T
PLoS ONE 2018; 13: e0198830 (IGR: 19-4)


77687 Noninvasive Detection of Mitochondrial Dysfunction in Ocular Hypertension and Primary Open-angle Glaucoma
Krawitz BD
Journal of Glaucoma 2018; 27: 592-599 (IGR: 19-4)


78207 Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma
Gisler C
American Journal of Ophthalmology 2018; 194: 46-53 (IGR: 19-4)


77956 Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning
Asaoka R
American Journal of Ophthalmology 2018; 193: 71-79 (IGR: 19-4)


78207 Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma
Hennebert J
American Journal of Ophthalmology 2018; 194: 46-53 (IGR: 19-4)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Nishiguchi KM
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


77893 Investigation of lateral geniculate nucleus volume and diffusion tensor imaging in patients with normal tension glaucoma using 7 tesla magnetic resonance imaging
Dörfler A
PLoS ONE 2018; 13: e0198830 (IGR: 19-4)


77956 Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning
Murata H
American Journal of Ophthalmology 2018; 193: 71-79 (IGR: 19-4)


77687 Noninvasive Detection of Mitochondrial Dysfunction in Ocular Hypertension and Primary Open-angle Glaucoma
Mo S; Pinhas A
Journal of Glaucoma 2018; 27: 592-599 (IGR: 19-4)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Murata T
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


77893 Investigation of lateral geniculate nucleus volume and diffusion tensor imaging in patients with normal tension glaucoma using 7 tesla magnetic resonance imaging
Engelhorn T
PLoS ONE 2018; 13: e0198830 (IGR: 19-4)


77956 Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning
Lemij H
American Journal of Ophthalmology 2018; 193: 71-79 (IGR: 19-4)


78207 Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma
Genoud D
American Journal of Ophthalmology 2018; 194: 46-53 (IGR: 19-4)


77687 Noninvasive Detection of Mitochondrial Dysfunction in Ocular Hypertension and Primary Open-angle Glaucoma
Ritch R
Journal of Glaucoma 2018; 27: 592-599 (IGR: 19-4)


78207 Use of Machine Learning on Contact Lens Sensor-Derived Parameters for the Diagnosis of Primary Open-angle Glaucoma

American Journal of Ophthalmology 2018; 194: 46-53 (IGR: 19-4)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Taki Y
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


77956 Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning
Yamanishi K
American Journal of Ophthalmology 2018; 193: 71-79 (IGR: 19-4)


78084 Quantitative MRI evaluation of glaucomatous changes in the visual pathway
Nakazawa T
PLoS ONE 2018; 13: e0197027 (IGR: 19-4)


77687 Noninvasive Detection of Mitochondrial Dysfunction in Ocular Hypertension and Primary Open-angle Glaucoma
Rosen RB
Journal of Glaucoma 2018; 27: 592-599 (IGR: 19-4)


76966 Reduced Functional and Anatomic Interhemispheric Homotopic Connectivity in Primary Open-Angle Glaucoma: A Combined Resting State-fMRI and DTI Study
Wang Q
Investigative Ophthalmology and Visual Science 2018; 59: 1861-1868 (IGR: 19-3)


76887 Intraocular light scatter in patients on topical intraocular pressure-lowering medication
Pérez-Bartolomé F
European Journal of Ophthalmology 2018; 0: 1120672117753667 (IGR: 19-3)


77237 Active Lymphatic Drainage From the Eye Measured by Noninvasive Photoacoustic Imaging of Near-Infrared Nanoparticles
Yücel YH
Investigative Ophthalmology and Visual Science 2018; 59: 2699-2707 (IGR: 19-3)


76875 White Matter Abnormalities and Correlation With Severity in Normal Tension Glaucoma: A Whole Brain Atlas-Based Diffusion Tensor Study
Wang R
Investigative Ophthalmology and Visual Science 2018; 59: 1313-1322 (IGR: 19-3)


76880 Assessment of Corneal Changes Associated with Topical Antiglaucoma Therapy Using in vivo Confocal Microscopy
Baghdasaryan E
Ophthalmic Research 2018; 0: (IGR: 19-3)


76534 Microstructural visual pathway abnormalities in patients with primary glaucoma: 3 T diffusion kurtosis imaging study
Xu ZF
Clinical radiology 2018; 73: 591.e9-591.e15 (IGR: 19-3)


77260 Real-Time Imaging of Retinal Cell Apoptosis by Confocal Scanning Laser Ophthalmoscopy and Its Role in Glaucoma
Yang E
Frontiers in neurology 2018; 9: 338 (IGR: 19-3)


77237 Active Lymphatic Drainage From the Eye Measured by Noninvasive Photoacoustic Imaging of Near-Infrared Nanoparticles
Cardinell K
Investigative Ophthalmology and Visual Science 2018; 59: 2699-2707 (IGR: 19-3)


76534 Microstructural visual pathway abnormalities in patients with primary glaucoma: 3 T diffusion kurtosis imaging study
Sun JS
Clinical radiology 2018; 73: 591.e9-591.e15 (IGR: 19-3)


76887 Intraocular light scatter in patients on topical intraocular pressure-lowering medication
Martínez de la Casa JM
European Journal of Ophthalmology 2018; 0: 1120672117753667 (IGR: 19-3)


76875 White Matter Abnormalities and Correlation With Severity in Normal Tension Glaucoma: A Whole Brain Atlas-Based Diffusion Tensor Study
Tang Z
Investigative Ophthalmology and Visual Science 2018; 59: 1313-1322 (IGR: 19-3)


76966 Reduced Functional and Anatomic Interhemispheric Homotopic Connectivity in Primary Open-Angle Glaucoma: A Combined Resting State-fMRI and DTI Study
Chen W
Investigative Ophthalmology and Visual Science 2018; 59: 1861-1868 (IGR: 19-3)


77260 Real-Time Imaging of Retinal Cell Apoptosis by Confocal Scanning Laser Ophthalmoscopy and Its Role in Glaucoma
Al-Mugheiry TS
Frontiers in neurology 2018; 9: 338 (IGR: 19-3)


76880 Assessment of Corneal Changes Associated with Topical Antiglaucoma Therapy Using in vivo Confocal Microscopy
Tepelus TC
Ophthalmic Research 2018; 0: (IGR: 19-3)


76875 White Matter Abnormalities and Correlation With Severity in Normal Tension Glaucoma: A Whole Brain Atlas-Based Diffusion Tensor Study
Sun X
Investigative Ophthalmology and Visual Science 2018; 59: 1313-1322 (IGR: 19-3)


77260 Real-Time Imaging of Retinal Cell Apoptosis by Confocal Scanning Laser Ophthalmoscopy and Its Role in Glaucoma
Normando EM
Frontiers in neurology 2018; 9: 338 (IGR: 19-3)


76966 Reduced Functional and Anatomic Interhemispheric Homotopic Connectivity in Primary Open-Angle Glaucoma: A Combined Resting State-fMRI and DTI Study
Wang H
Investigative Ophthalmology and Visual Science 2018; 59: 1861-1868 (IGR: 19-3)


76887 Intraocular light scatter in patients on topical intraocular pressure-lowering medication
Arriola-Villalobos P
European Journal of Ophthalmology 2018; 0: 1120672117753667 (IGR: 19-3)


76534 Microstructural visual pathway abnormalities in patients with primary glaucoma: 3 T diffusion kurtosis imaging study
Zhang XH
Clinical radiology 2018; 73: 591.e9-591.e15 (IGR: 19-3)


77237 Active Lymphatic Drainage From the Eye Measured by Noninvasive Photoacoustic Imaging of Near-Infrared Nanoparticles
Khattak S
Investigative Ophthalmology and Visual Science 2018; 59: 2699-2707 (IGR: 19-3)


76880 Assessment of Corneal Changes Associated with Topical Antiglaucoma Therapy Using in vivo Confocal Microscopy
Vickers LA
Ophthalmic Research 2018; 0: (IGR: 19-3)


76887 Intraocular light scatter in patients on topical intraocular pressure-lowering medication
Fernández-Pérez C
European Journal of Ophthalmology 2018; 0: 1120672117753667 (IGR: 19-3)


77237 Active Lymphatic Drainage From the Eye Measured by Noninvasive Photoacoustic Imaging of Near-Infrared Nanoparticles
Zhou X
Investigative Ophthalmology and Visual Science 2018; 59: 2699-2707 (IGR: 19-3)


77260 Real-Time Imaging of Retinal Cell Apoptosis by Confocal Scanning Laser Ophthalmoscopy and Its Role in Glaucoma
Cordeiro MF
Frontiers in neurology 2018; 9: 338 (IGR: 19-3)


76875 White Matter Abnormalities and Correlation With Severity in Normal Tension Glaucoma: A Whole Brain Atlas-Based Diffusion Tensor Study
Wu L
Investigative Ophthalmology and Visual Science 2018; 59: 1313-1322 (IGR: 19-3)


76880 Assessment of Corneal Changes Associated with Topical Antiglaucoma Therapy Using in vivo Confocal Microscopy
Huang P
Ophthalmic Research 2018; 0: (IGR: 19-3)


76534 Microstructural visual pathway abnormalities in patients with primary glaucoma: 3 T diffusion kurtosis imaging study
Feng YY
Clinical radiology 2018; 73: 591.e9-591.e15 (IGR: 19-3)


76966 Reduced Functional and Anatomic Interhemispheric Homotopic Connectivity in Primary Open-Angle Glaucoma: A Combined Resting State-fMRI and DTI Study
Zhang X; Qu X
Investigative Ophthalmology and Visual Science 2018; 59: 1861-1868 (IGR: 19-3)


76534 Microstructural visual pathway abnormalities in patients with primary glaucoma: 3 T diffusion kurtosis imaging study
Pan AZ
Clinical radiology 2018; 73: 591.e9-591.e15 (IGR: 19-3)


77237 Active Lymphatic Drainage From the Eye Measured by Noninvasive Photoacoustic Imaging of Near-Infrared Nanoparticles
Lapinski M
Investigative Ophthalmology and Visual Science 2018; 59: 2699-2707 (IGR: 19-3)


76887 Intraocular light scatter in patients on topical intraocular pressure-lowering medication
García-Feijoó J
European Journal of Ophthalmology 2018; 0: 1120672117753667 (IGR: 19-3)


76875 White Matter Abnormalities and Correlation With Severity in Normal Tension Glaucoma: A Whole Brain Atlas-Based Diffusion Tensor Study
Wang J
Investigative Ophthalmology and Visual Science 2018; 59: 1313-1322 (IGR: 19-3)


76880 Assessment of Corneal Changes Associated with Topical Antiglaucoma Therapy Using in vivo Confocal Microscopy
Chopra V
Ophthalmic Research 2018; 0: (IGR: 19-3)


76875 White Matter Abnormalities and Correlation With Severity in Normal Tension Glaucoma: A Whole Brain Atlas-Based Diffusion Tensor Study
Zhong Y
Investigative Ophthalmology and Visual Science 2018; 59: 1313-1322 (IGR: 19-3)


76880 Assessment of Corneal Changes Associated with Topical Antiglaucoma Therapy Using in vivo Confocal Microscopy
Sadda SR
Ophthalmic Research 2018; 0: (IGR: 19-3)


76966 Reduced Functional and Anatomic Interhemispheric Homotopic Connectivity in Primary Open-Angle Glaucoma: A Combined Resting State-fMRI and DTI Study
Wang Y
Investigative Ophthalmology and Visual Science 2018; 59: 1861-1868 (IGR: 19-3)


76534 Microstructural visual pathway abnormalities in patients with primary glaucoma: 3 T diffusion kurtosis imaging study
Gao MY
Clinical radiology 2018; 73: 591.e9-591.e15 (IGR: 19-3)


77237 Active Lymphatic Drainage From the Eye Measured by Noninvasive Photoacoustic Imaging of Near-Infrared Nanoparticles
Cheng F; Gupta N
Investigative Ophthalmology and Visual Science 2018; 59: 2699-2707 (IGR: 19-3)


76534 Microstructural visual pathway abnormalities in patients with primary glaucoma: 3 T diffusion kurtosis imaging study
Zhao H
Clinical radiology 2018; 73: 591.e9-591.e15 (IGR: 19-3)


76880 Assessment of Corneal Changes Associated with Topical Antiglaucoma Therapy Using in vivo Confocal Microscopy
Lee OL
Ophthalmic Research 2018; 0: (IGR: 19-3)


76966 Reduced Functional and Anatomic Interhemispheric Homotopic Connectivity in Primary Open-Angle Glaucoma: A Combined Resting State-fMRI and DTI Study
Li T
Investigative Ophthalmology and Visual Science 2018; 59: 1861-1868 (IGR: 19-3)


76875 White Matter Abnormalities and Correlation With Severity in Normal Tension Glaucoma: A Whole Brain Atlas-Based Diffusion Tensor Study
Xiao Z
Investigative Ophthalmology and Visual Science 2018; 59: 1313-1322 (IGR: 19-3)


76966 Reduced Functional and Anatomic Interhemispheric Homotopic Connectivity in Primary Open-Angle Glaucoma: A Combined Resting State-fMRI and DTI Study
Wang N; Xian J
Investigative Ophthalmology and Visual Science 2018; 59: 1861-1868 (IGR: 19-3)


75275 Signal Alteration in the Optic Nerve Head on 3D T2-weighted MRI: a Potential Neuroimaging Sign of Glaucomatous Optic Neuropathy
Lee JY
Current Eye Research 2018; 43: 397-405 (IGR: 19-2)


75373 Flow dynamics of cerebrospinal fluid between the intracranial cavity and the subarachnoid space of the optic nerve measured with a diffusion magnetic resonance imaging sequence in patients with normal tension glaucoma
Boye D
Clinical and Experimental Ophthalmology 2018; 46: 511-518 (IGR: 19-2)


75275 Signal Alteration in the Optic Nerve Head on 3D T2-weighted MRI: a Potential Neuroimaging Sign of Glaucomatous Optic Neuropathy
Kwon HJ
Current Eye Research 2018; 43: 397-405 (IGR: 19-2)


75373 Flow dynamics of cerebrospinal fluid between the intracranial cavity and the subarachnoid space of the optic nerve measured with a diffusion magnetic resonance imaging sequence in patients with normal tension glaucoma
Montali M; Miller NR
Clinical and Experimental Ophthalmology 2018; 46: 511-518 (IGR: 19-2)


75275 Signal Alteration in the Optic Nerve Head on 3D T2-weighted MRI: a Potential Neuroimaging Sign of Glaucomatous Optic Neuropathy
Park SJ; Yoo C
Current Eye Research 2018; 43: 397-405 (IGR: 19-2)


75373 Flow dynamics of cerebrospinal fluid between the intracranial cavity and the subarachnoid space of the optic nerve measured with a diffusion magnetic resonance imaging sequence in patients with normal tension glaucoma
Pircher A
Clinical and Experimental Ophthalmology 2018; 46: 511-518 (IGR: 19-2)


75275 Signal Alteration in the Optic Nerve Head on 3D T2-weighted MRI: a Potential Neuroimaging Sign of Glaucomatous Optic Neuropathy
Kim YY
Current Eye Research 2018; 43: 397-405 (IGR: 19-2)


75373 Flow dynamics of cerebrospinal fluid between the intracranial cavity and the subarachnoid space of the optic nerve measured with a diffusion magnetic resonance imaging sequence in patients with normal tension glaucoma
Gruber P
Clinical and Experimental Ophthalmology 2018; 46: 511-518 (IGR: 19-2)


75275 Signal Alteration in the Optic Nerve Head on 3D T2-weighted MRI: a Potential Neuroimaging Sign of Glaucomatous Optic Neuropathy
Kim EY
Current Eye Research 2018; 43: 397-405 (IGR: 19-2)


75373 Flow dynamics of cerebrospinal fluid between the intracranial cavity and the subarachnoid space of the optic nerve measured with a diffusion magnetic resonance imaging sequence in patients with normal tension glaucoma
Killer HE; Remonda L; Berberat J
Clinical and Experimental Ophthalmology 2018; 46: 511-518 (IGR: 19-2)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Hondur G
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Demer JL
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74357 Evaluation of Bleb Fluid After Baerveldt Glaucoma Implantation Using Magnetic Resonance Imaging
Iwasaki K
Scientific reports 2017; 7: 11345 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Göktas E
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Clark RA
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74357 Evaluation of Bleb Fluid After Baerveldt Glaucoma Implantation Using Magnetic Resonance Imaging
Kanamoto M
Scientific reports 2017; 7: 11345 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Suh SY
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Yang X
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74357 Evaluation of Bleb Fluid After Baerveldt Glaucoma Implantation Using Magnetic Resonance Imaging
Takihara Y
Scientific reports 2017; 7: 11345 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Al-Aswad L
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74357 Evaluation of Bleb Fluid After Baerveldt Glaucoma Implantation Using Magnetic Resonance Imaging
Arimura S
Scientific reports 2017; 7: 11345 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Giaconi JA
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74357 Evaluation of Bleb Fluid After Baerveldt Glaucoma Implantation Using Magnetic Resonance Imaging
Takamura Y
Scientific reports 2017; 7: 11345 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Nouri-Mahdavi K
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Auran JD
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Law SK
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Blumberg DM
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74357 Evaluation of Bleb Fluid After Baerveldt Glaucoma Implantation Using Magnetic Resonance Imaging
Kimura H; Inatani M
Scientific reports 2017; 7: 11345 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Cioffi GA
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Bonelli L
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Liebmann JM
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Coleman AL
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Suh LH
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


74199 Magnetic Resonance Imaging of Optic Nerve Traction During Adduction in Primary Open-Angle Glaucoma With Normal Intraocular Pressure
Caprioli J
Investigative Ophthalmology and Visual Science 2017; 58: 4114-4125 (IGR: 19-1)


74184 Oxidative Stress-Related Molecular Biomarker Candidates for Glaucoma
Trief D; Tezel G
Investigative Ophthalmology and Visual Science 2017; 58: 4078-4088 (IGR: 19-1)


72963 Relationship between the optic nerve sheath diameter and lumbar cerebrospinal fluid pressure in patients with normal tension glaucoma
Pircher A
Eye 2017; 31: 1365-1372 (IGR: 18-4)


72699 Magnetic Resonance Imaging Characteristics of a Baerveldt Glaucoma Implant
Anderson DM
Journal of Glaucoma 2017; 26: 534-540 (IGR: 18-4)


72954 Disrupted Eye Movements in Preperimetric Primary Open-Angle Glaucoma
Najjar RP
Investigative Ophthalmology and Visual Science 2017; 58: 2430-2437 (IGR: 18-4)


72713 An introduction to DARC technology
Ahmad SS
Saudi Journal of Ophthalmology 2017; 31: 38-41 (IGR: 18-4)


72963 Relationship between the optic nerve sheath diameter and lumbar cerebrospinal fluid pressure in patients with normal tension glaucoma
Montali M
Eye 2017; 31: 1365-1372 (IGR: 18-4)


72699 Magnetic Resonance Imaging Characteristics of a Baerveldt Glaucoma Implant
Schwope RB
Journal of Glaucoma 2017; 26: 534-540 (IGR: 18-4)


72954 Disrupted Eye Movements in Preperimetric Primary Open-Angle Glaucoma
Sharma S; Drouet M
Investigative Ophthalmology and Visual Science 2017; 58: 2430-2437 (IGR: 18-4)


72963 Relationship between the optic nerve sheath diameter and lumbar cerebrospinal fluid pressure in patients with normal tension glaucoma
Berberat J
Eye 2017; 31: 1365-1372 (IGR: 18-4)


72699 Magnetic Resonance Imaging Characteristics of a Baerveldt Glaucoma Implant
Reiter MJ
Journal of Glaucoma 2017; 26: 534-540 (IGR: 18-4)


72954 Disrupted Eye Movements in Preperimetric Primary Open-Angle Glaucoma
Leruez S
Investigative Ophthalmology and Visual Science 2017; 58: 2430-2437 (IGR: 18-4)


72963 Relationship between the optic nerve sheath diameter and lumbar cerebrospinal fluid pressure in patients with normal tension glaucoma
Remonda L
Eye 2017; 31: 1365-1372 (IGR: 18-4)


72699 Magnetic Resonance Imaging Characteristics of a Baerveldt Glaucoma Implant
Suhr AW
Journal of Glaucoma 2017; 26: 534-540 (IGR: 18-4)


72963 Relationship between the optic nerve sheath diameter and lumbar cerebrospinal fluid pressure in patients with normal tension glaucoma
Killer HE
Eye 2017; 31: 1365-1372 (IGR: 18-4)


72954 Disrupted Eye Movements in Preperimetric Primary Open-Angle Glaucoma
Baskaran M; Nongpiur ME; Aung T; Fielding J; White O; Girard MJ; Lamirel C; Milea D
Investigative Ophthalmology and Visual Science 2017; 58: 2430-2437 (IGR: 18-4)


71057 MRI Study of the Posterior Visual Pathways in Primary Open Angle Glaucoma
Zhou W
Journal of Glaucoma 2017; 26: 173-181 (IGR: 18-3)


71322 Comparison of anterior segment measurements with LenStar and Pentacam in patients with newly diagnosed glaucoma
Sen E
International Ophthalmology 2018; 38: 171-174 (IGR: 18-3)


71535 Retinotopic fMRI Reveals Visual Dysfunction and Functional Reorganization in the Visual Cortex of Mild to Moderate Glaucoma Patients
Zhou W
Journal of Glaucoma 2017; 26: 430-437 (IGR: 18-3)


71530 Study of optic radiations in patients with primary open-angle glaucoma with diffusion tensor imaging
Li T
Zhonghua Yi Xue Za Zhi 2017; 97: 347-352 (IGR: 18-3)


71613 Diffusion tensor imaging of the visual pathway in glaucomatous optic nerve atrophy
Engelhorn T
Ophthalmologe 2017; 114: 906-921 (IGR: 18-3)


71605 Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging
Jiang MM
Medicine 2017; 96: e6139 (IGR: 18-3)


71613 Diffusion tensor imaging of the visual pathway in glaucomatous optic nerve atrophy
A Schmidt M
Ophthalmologe 2017; 114: 906-921 (IGR: 18-3)


71057 MRI Study of the Posterior Visual Pathways in Primary Open Angle Glaucoma
Muir ER
Journal of Glaucoma 2017; 26: 173-181 (IGR: 18-3)


71530 Study of optic radiations in patients with primary open-angle glaucoma with diffusion tensor imaging
Miao W
Zhonghua Yi Xue Za Zhi 2017; 97: 347-352 (IGR: 18-3)


71605 Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging
Zhou Q
Medicine 2017; 96: e6139 (IGR: 18-3)


71535 Retinotopic fMRI Reveals Visual Dysfunction and Functional Reorganization in the Visual Cortex of Mild to Moderate Glaucoma Patients
Muir ER
Journal of Glaucoma 2017; 26: 430-437 (IGR: 18-3)


71322 Comparison of anterior segment measurements with LenStar and Pentacam in patients with newly diagnosed glaucoma
Inanc M
International Ophthalmology 2018; 38: 171-174 (IGR: 18-3)


71530 Study of optic radiations in patients with primary open-angle glaucoma with diffusion tensor imaging
He HG
Zhonghua Yi Xue Za Zhi 2017; 97: 347-352 (IGR: 18-3)


71605 Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging
Liu XY
Medicine 2017; 96: e6139 (IGR: 18-3)


71613 Diffusion tensor imaging of the visual pathway in glaucomatous optic nerve atrophy
Dörfler A
Ophthalmologe 2017; 114: 906-921 (IGR: 18-3)


71322 Comparison of anterior segment measurements with LenStar and Pentacam in patients with newly diagnosed glaucoma
Elgin U
International Ophthalmology 2018; 38: 171-174 (IGR: 18-3)


71535 Retinotopic fMRI Reveals Visual Dysfunction and Functional Reorganization in the Visual Cortex of Mild to Moderate Glaucoma Patients
Nagi KS
Journal of Glaucoma 2017; 26: 430-437 (IGR: 18-3)


71057 MRI Study of the Posterior Visual Pathways in Primary Open Angle Glaucoma
Chalfin S
Journal of Glaucoma 2017; 26: 173-181 (IGR: 18-3)


71613 Diffusion tensor imaging of the visual pathway in glaucomatous optic nerve atrophy
Michelson G
Ophthalmologe 2017; 114: 906-921 (IGR: 18-3)


71322 Comparison of anterior segment measurements with LenStar and Pentacam in patients with newly diagnosed glaucoma
Yilmazbas P
International Ophthalmology 2018; 38: 171-174 (IGR: 18-3)


71535 Retinotopic fMRI Reveals Visual Dysfunction and Functional Reorganization in the Visual Cortex of Mild to Moderate Glaucoma Patients
Chalfin S
Journal of Glaucoma 2017; 26: 430-437 (IGR: 18-3)


71057 MRI Study of the Posterior Visual Pathways in Primary Open Angle Glaucoma
Nagi KS
Journal of Glaucoma 2017; 26: 173-181 (IGR: 18-3)


71605 Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging
Shi CZ
Medicine 2017; 96: e6139 (IGR: 18-3)


71530 Study of optic radiations in patients with primary open-angle glaucoma with diffusion tensor imaging
Xian JF
Zhonghua Yi Xue Za Zhi 2017; 97: 347-352 (IGR: 18-3)


71535 Retinotopic fMRI Reveals Visual Dysfunction and Functional Reorganization in the Visual Cortex of Mild to Moderate Glaucoma Patients
Rodriguez P
Journal of Glaucoma 2017; 26: 430-437 (IGR: 18-3)


71605 Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging
Chen J
Medicine 2017; 96: e6139 (IGR: 18-3)


71057 MRI Study of the Posterior Visual Pathways in Primary Open Angle Glaucoma
Duong TQ
Journal of Glaucoma 2017; 26: 173-181 (IGR: 18-3)


71535 Retinotopic fMRI Reveals Visual Dysfunction and Functional Reorganization in the Visual Cortex of Mild to Moderate Glaucoma Patients
Duong TQ
Journal of Glaucoma 2017; 26: 430-437 (IGR: 18-3)


71605 Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging
Huang XH
Medicine 2017; 96: e6139 (IGR: 18-3)


70325 Altered functional connectivity within and between the default model network and the visual network in primary open-angle glaucoma: a resting-state fMRI study
Wang J
Brain imaging and behavior 2017; 11: 1154-1163 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Tellouck L
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Murphy MC
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Ho LC
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70360 Imaging characteristics of the postoperative globe: a pictorial essay
Ito Y
Japanese journal of radiology 2016; 34: 779-785 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Li S
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


70333 Intraocular Pressure Induced Retinal Changes Identified Using Synchrotron Infrared Microscopy
Shen HH
PLoS ONE 2016; 11: e0164035 (IGR: 18-2)


69957 Early changes of brain connectivity in primary open angle glaucoma
Frezzotti P
Human Brain Mapping 2016; 37: 4581-4596 (IGR: 18-2)


70163 Magnetic Resonance Imaging of Cyclodialysis Cleft Before and After Cyclopexy
Jeong JH
Journal of Glaucoma 2017; 26: e15-e18 (IGR: 18-2)


70333 Intraocular Pressure Induced Retinal Changes Identified Using Synchrotron Infrared Microscopy
Liu GS
PLoS ONE 2016; 11: e0164035 (IGR: 18-2)


69957 Early changes of brain connectivity in primary open angle glaucoma
Giorgio A
Human Brain Mapping 2016; 37: 4581-4596 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Durieux M
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70163 Magnetic Resonance Imaging of Cyclodialysis Cleft Before and After Cyclopexy
Jeoung JW
Journal of Glaucoma 2017; 26: e15-e18 (IGR: 18-2)


70325 Altered functional connectivity within and between the default model network and the visual network in primary open-angle glaucoma: a resting-state fMRI study
Li T
Brain imaging and behavior 2017; 11: 1154-1163 (IGR: 18-2)


70360 Imaging characteristics of the postoperative globe: a pictorial essay
Yamazaki I
Japanese journal of radiology 2016; 34: 779-785 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Sigal IA
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Li P
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Conner IP
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Gong H
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


70360 Imaging characteristics of the postoperative globe: a pictorial essay
Kikuchi Y
Japanese journal of radiology 2016; 34: 779-785 (IGR: 18-2)


70333 Intraocular Pressure Induced Retinal Changes Identified Using Synchrotron Infrared Microscopy
Chow SH
PLoS ONE 2016; 11: e0164035 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Jan NJ
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70163 Magnetic Resonance Imaging of Cyclodialysis Cleft Before and After Cyclopexy
Moon NJ
Journal of Glaucoma 2017; 26: e15-e18 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Teng CY
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Coupé P
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


69957 Early changes of brain connectivity in primary open angle glaucoma
Toto F
Human Brain Mapping 2016; 37: 4581-4596 (IGR: 18-2)


70325 Altered functional connectivity within and between the default model network and the visual network in primary open-angle glaucoma: a resting-state fMRI study
Zhou P
Brain imaging and behavior 2017; 11: 1154-1163 (IGR: 18-2)


70360 Imaging characteristics of the postoperative globe: a pictorial essay
O'uchi E
Japanese journal of radiology 2016; 34: 779-785 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Cougnard-Grégoire A
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Yang X
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Jiang F
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Lawrence JD
Scientific reports 2016; 6: 31464 (IGR: 18-2)


69957 Early changes of brain connectivity in primary open angle glaucoma
De Leucio A
Human Brain Mapping 2016; 37: 4581-4596 (IGR: 18-2)


70325 Altered functional connectivity within and between the default model network and the visual network in primary open-angle glaucoma: a resting-state fMRI study
Wang N
Brain imaging and behavior 2017; 11: 1154-1163 (IGR: 18-2)


70333 Intraocular Pressure Induced Retinal Changes Identified Using Synchrotron Infrared Microscopy
Wang JH
PLoS ONE 2016; 11: e0164035 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Safiullah Z
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70333 Intraocular Pressure Induced Retinal Changes Identified Using Synchrotron Infrared Microscopy
He Z
PLoS ONE 2016; 11: e0164035 (IGR: 18-2)


70325 Altered functional connectivity within and between the default model network and the visual network in primary open-angle glaucoma: a resting-state fMRI study
Xian J
Brain imaging and behavior 2017; 11: 1154-1163 (IGR: 18-2)


69957 Early changes of brain connectivity in primary open angle glaucoma
De Stefano N
Human Brain Mapping 2016; 37: 4581-4596 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Tellouck J
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Liu D
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
van der Merwe Y
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70360 Imaging characteristics of the postoperative globe: a pictorial essay
O'uchi T; Kato H
Japanese journal of radiology 2016; 34: 779-785 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Cai F
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


70333 Intraocular Pressure Induced Retinal Changes Identified Using Synchrotron Infrared Microscopy
Nguyen C
PLoS ONE 2016; 11: e0164035 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Wang B
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70325 Altered functional connectivity within and between the default model network and the visual network in primary open-angle glaucoma: a resting-state fMRI study
He H
Brain imaging and behavior 2017; 11: 1154-1163 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Tourdias T
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Yu Y
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Pei C
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


70333 Intraocular Pressure Induced Retinal Changes Identified Using Synchrotron Infrared Microscopy
Lin TW
PLoS ONE 2016; 11: e0164035 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Munsch F
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Chau Y
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70360 Imaging characteristics of the postoperative globe: a pictorial essay
Hotta K
Japanese journal of radiology 2016; 34: 779-785 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Bilonick RA
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Garrigues A
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Leung CK
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Zhou F
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


70333 Intraocular Pressure Induced Retinal Changes Identified Using Synchrotron Infrared Microscopy
Bui BV
PLoS ONE 2016; 11: e0164035 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Kim SG
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Conner IP
Scientific reports 2016; 6: 32080 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Wollstein G
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Helmer C
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70904 Intrinsic Functional Connectivity Alterations of the Primary Visual Cortex in Primary Angle-Closure Glaucoma Patients before and after Surgery: A Resting-State fMRI Study
Zeng X
PLoS ONE 2017; 12: e0170598 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Schuman JS
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Malet F
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Jin T
Scientific reports 2016; 6: 32080 (IGR: 18-2)


69972 Retinal Structures and Visual Cortex Activity are Impaired Prior to Clinical Vision Loss in Glaucoma
Chan KC
Scientific reports 2016; 6: 31464 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Wu EX
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Dartigues JF
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Kim SG
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Dousset V
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Wollstein G
Scientific reports 2016; 6: 32080 (IGR: 18-2)


70679 Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging
Delcourt C; Schweitzer C
Investigative Ophthalmology and Visual Science 2016; 57: 6539-6547 (IGR: 18-2)


70088 Non-invasive MRI Assessments of Tissue Microstructures and Macromolecules in the Eye upon Biomechanical or Biochemical Modulation
Schuman JS; Chan KC
Scientific reports 2016; 6: 32080 (IGR: 18-2)


68913 Elevated neutrophil-to-lymphocyte ratio in pseudoexfoliation syndrome
Kurtul BE; Ozer PA; Kabatas EU
Eye 2016; 30: 1045-1048 (IGR: 18-1)


66684 In vivo characterization of lamina cribrosa pore morphology in primary open-angle glaucoma
Zwillinger S
Journal Franšais d'Ophtalmologie 2016; 39: 265-271 (IGR: 17-4)


67508 Using magnetic resonance imaging to assess visual deficits: a review
Brown HD
Ophthalmic and Physiological Optics 2016; 36: 240-265 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Ji Y
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


66724 Primary Open Angle Glaucoma is Associated with MR Biomarkers of Cerebral Small Vessel Disease
Mercieca K
Scientific reports 2016; 6: 22160 (IGR: 17-4)


66808 Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients
Wang J
European radiology 2016; 26: 3957-3967 (IGR: 17-4)


67315 In vivo proton magnetic resonance spectroscopy (1H-MRS) evaluation of the metabolite concentration of optic radiation in primary open angle glaucoma
Sidek S
European radiology 2016; 26: 4404-4412 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Zuo C
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67315 In vivo proton magnetic resonance spectroscopy (1H-MRS) evaluation of the metabolite concentration of optic radiation in primary open angle glaucoma
Ramli N
European radiology 2016; 26: 4404-4412 (IGR: 17-4)


67508 Using magnetic resonance imaging to assess visual deficits: a review
Woodall RL
Ophthalmic and Physiological Optics 2016; 36: 240-265 (IGR: 17-4)


66684 In vivo characterization of lamina cribrosa pore morphology in primary open-angle glaucoma
Paques M
Journal Franšais d'Ophtalmologie 2016; 39: 265-271 (IGR: 17-4)


66808 Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients
Li T
European radiology 2016; 26: 3957-3967 (IGR: 17-4)


66724 Primary Open Angle Glaucoma is Associated with MR Biomarkers of Cerebral Small Vessel Disease
Cain J
Scientific reports 2016; 6: 22160 (IGR: 17-4)


66808 Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients
Wang N
European radiology 2016; 26: 3957-3967 (IGR: 17-4)


66684 In vivo characterization of lamina cribrosa pore morphology in primary open-angle glaucoma
Safran B
Journal Franšais d'Ophtalmologie 2016; 39: 265-271 (IGR: 17-4)


66724 Primary Open Angle Glaucoma is Associated with MR Biomarkers of Cerebral Small Vessel Disease
Hansen T
Scientific reports 2016; 6: 22160 (IGR: 17-4)


67315 In vivo proton magnetic resonance spectroscopy (1H-MRS) evaluation of the metabolite concentration of optic radiation in primary open angle glaucoma
Rahmat K
European radiology 2016; 26: 4404-4412 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Lin M
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67508 Using magnetic resonance imaging to assess visual deficits: a review
Kitching RE
Ophthalmic and Physiological Optics 2016; 36: 240-265 (IGR: 17-4)


67315 In vivo proton magnetic resonance spectroscopy (1H-MRS) evaluation of the metabolite concentration of optic radiation in primary open angle glaucoma
Ramli NM
European radiology 2016; 26: 4404-4412 (IGR: 17-4)


66724 Primary Open Angle Glaucoma is Associated with MR Biomarkers of Cerebral Small Vessel Disease
Steeples L
Scientific reports 2016; 6: 22160 (IGR: 17-4)


67508 Using magnetic resonance imaging to assess visual deficits: a review
Baseler HA
Ophthalmic and Physiological Optics 2016; 36: 240-265 (IGR: 17-4)


66808 Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients
Xian J
European radiology 2016; 26: 3957-3967 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Zhang X
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


66684 In vivo characterization of lamina cribrosa pore morphology in primary open-angle glaucoma
Baudouin C
Journal Franšais d'Ophtalmologie 2016; 39: 265-271 (IGR: 17-4)


66724 Primary Open Angle Glaucoma is Associated with MR Biomarkers of Cerebral Small Vessel Disease
Watkins A
Scientific reports 2016; 6: 22160 (IGR: 17-4)


67315 In vivo proton magnetic resonance spectroscopy (1H-MRS) evaluation of the metabolite concentration of optic radiation in primary open angle glaucoma
Abdulrahman F
European radiology 2016; 26: 4404-4412 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Li M
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


67508 Using magnetic resonance imaging to assess visual deficits: a review
Morland AB
Ophthalmic and Physiological Optics 2016; 36: 240-265 (IGR: 17-4)


66808 Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients
He H
European radiology 2016; 26: 3957-3967 (IGR: 17-4)


67315 In vivo proton magnetic resonance spectroscopy (1H-MRS) evaluation of the metabolite concentration of optic radiation in primary open angle glaucoma
Kuo TL
European radiology 2016; 26: 4404-4412 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Mi L
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


66724 Primary Open Angle Glaucoma is Associated with MR Biomarkers of Cerebral Small Vessel Disease
Spencer F; Jackson A
Scientific reports 2016; 6: 22160 (IGR: 17-4)


67459 Macular Pigment Optical Density in Chinese Primary Open Angle Glaucoma Using the One-Wavelength Reflectometry Method
Liu B; Wen F
Journal of Ophthalmology 2016; 2016: 2792103 (IGR: 17-4)


66553 Diaphanoscopy in cyclophotocoagulation
Wecker T
Ophthalmologe 2016; 113: 171-174 (IGR: 17-3)


66383 Assessment of Filtration Bleb and Endplate Positioning Using Magnetic Resonance Imaging in Eyes Implanted with Long-Tube Glaucoma Drainage Devices
Sano I
PLoS ONE 2015; 10: e0144595 (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Wang J
Scientific reports 2016; 6: 18969 (IGR: 17-3)


65993 Selective reduction of fMRI responses to transient achromatic stimuli in the magnocellular layers of the LGN and the superficial layer of the SC of early glaucoma patients
Zhang P
Human Brain Mapping 2016; 37: 558-569 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Pavlatos E
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


66603 Saccadic vector optokinetic perimetry in children with neurodisability or isolated visual pathway lesions: observational cohort study
Tailor V
British Journal of Ophthalmology 2016; 100: 1427-1432 (IGR: 17-3)


66251 Aqueous Angiography: Real-Time and Physiologic Aqueous Humor Outflow Imaging
Saraswathy S
PLoS ONE 2016; 11: e0147176 (IGR: 17-3)


65903 Imaging mass spectrometry of the visual system: Advancing the molecular understanding of retina degenerations
Bowrey HE
Proteomics - Clinical Applications 2016; 10: 391-402 (IGR: 17-3)


66550 Anterior chamber aqueous flare, pseudoexfoliation syndrome, and glaucoma
Kahloun R
International Ophthalmology 2016; 36: 671-674 (IGR: 17-3)


65903 Imaging mass spectrometry of the visual system: Advancing the molecular understanding of retina degenerations
Anderson DM
Proteomics - Clinical Applications 2016; 10: 391-402 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Perez BC
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


66603 Saccadic vector optokinetic perimetry in children with neurodisability or isolated visual pathway lesions: observational cohort study
Glaze S
British Journal of Ophthalmology 2016; 100: 1427-1432 (IGR: 17-3)


66383 Assessment of Filtration Bleb and Endplate Positioning Using Magnetic Resonance Imaging in Eyes Implanted with Long-Tube Glaucoma Drainage Devices
Tanito M
PLoS ONE 2015; 10: e0144595 (IGR: 17-3)


66553 Diaphanoscopy in cyclophotocoagulation
Jordan JF
Ophthalmologe 2016; 113: 171-174 (IGR: 17-3)


66550 Anterior chamber aqueous flare, pseudoexfoliation syndrome, and glaucoma
Attia S
International Ophthalmology 2016; 36: 671-674 (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Li T
Scientific reports 2016; 6: 18969 (IGR: 17-3)


65993 Selective reduction of fMRI responses to transient achromatic stimuli in the magnocellular layers of the LGN and the superficial layer of the SC of early glaucoma patients
Wen W
Human Brain Mapping 2016; 37: 558-569 (IGR: 17-3)


66251 Aqueous Angiography: Real-Time and Physiologic Aqueous Humor Outflow Imaging
Tan JC
PLoS ONE 2016; 11: e0147176 (IGR: 17-3)


65993 Selective reduction of fMRI responses to transient achromatic stimuli in the magnocellular layers of the LGN and the superficial layer of the SC of early glaucoma patients
Sun X
Human Brain Mapping 2016; 37: 558-569 (IGR: 17-3)


66550 Anterior chamber aqueous flare, pseudoexfoliation syndrome, and glaucoma
Ksiaa I
International Ophthalmology 2016; 36: 671-674 (IGR: 17-3)


66251 Aqueous Angiography: Real-Time and Physiologic Aqueous Humor Outflow Imaging
Yu F
PLoS ONE 2016; 11: e0147176 (IGR: 17-3)


65903 Imaging mass spectrometry of the visual system: Advancing the molecular understanding of retina degenerations
Pallitto P
Proteomics - Clinical Applications 2016; 10: 391-402 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Morris HJ
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


66553 Diaphanoscopy in cyclophotocoagulation
van Oterendorp C
Ophthalmologe 2016; 113: 171-174 (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Sabel BA
Scientific reports 2016; 6: 18969 (IGR: 17-3)


66383 Assessment of Filtration Bleb and Endplate Positioning Using Magnetic Resonance Imaging in Eyes Implanted with Long-Tube Glaucoma Drainage Devices
Uchida K
PLoS ONE 2015; 10: e0144595 (IGR: 17-3)


66603 Saccadic vector optokinetic perimetry in children with neurodisability or isolated visual pathway lesions: observational cohort study
Unwin H; Bowman R
British Journal of Ophthalmology 2016; 100: 1427-1432 (IGR: 17-3)


65903 Imaging mass spectrometry of the visual system: Advancing the molecular understanding of retina degenerations
Gutierrez DB
Proteomics - Clinical Applications 2016; 10: 391-402 (IGR: 17-3)


66251 Aqueous Angiography: Real-Time and Physiologic Aqueous Humor Outflow Imaging
Francis BA
PLoS ONE 2016; 11: e0147176 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Chen H
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Chen Z
Scientific reports 2016; 6: 18969 (IGR: 17-3)


65993 Selective reduction of fMRI responses to transient achromatic stimuli in the magnocellular layers of the LGN and the superficial layer of the SC of early glaucoma patients
He S
Human Brain Mapping 2016; 37: 558-569 (IGR: 17-3)


66550 Anterior chamber aqueous flare, pseudoexfoliation syndrome, and glaucoma
Kacem I
International Ophthalmology 2016; 36: 671-674 (IGR: 17-3)


66383 Assessment of Filtration Bleb and Endplate Positioning Using Magnetic Resonance Imaging in Eyes Implanted with Long-Tube Glaucoma Drainage Devices
Katsube T
PLoS ONE 2015; 10: e0144595 (IGR: 17-3)


66251 Aqueous Angiography: Real-Time and Physiologic Aqueous Humor Outflow Imaging
Hinton DR
PLoS ONE 2016; 11: e0147176 (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Wen H
Scientific reports 2016; 6: 18969 (IGR: 17-3)


66383 Assessment of Filtration Bleb and Endplate Positioning Using Magnetic Resonance Imaging in Eyes Implanted with Long-Tube Glaucoma Drainage Devices
Kitagaki H
PLoS ONE 2015; 10: e0144595 (IGR: 17-3)


66550 Anterior chamber aqueous flare, pseudoexfoliation syndrome, and glaucoma
Bouanene I
International Ophthalmology 2016; 36: 671-674 (IGR: 17-3)


65903 Imaging mass spectrometry of the visual system: Advancing the molecular understanding of retina degenerations
Fan J
Proteomics - Clinical Applications 2016; 10: 391-402 (IGR: 17-3)


66603 Saccadic vector optokinetic perimetry in children with neurodisability or isolated visual pathway lesions: observational cohort study
Thompson G
British Journal of Ophthalmology 2016; 100: 1427-1432 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Palko JR
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


66550 Anterior chamber aqueous flare, pseudoexfoliation syndrome, and glaucoma
Zaouali S
International Ophthalmology 2016; 36: 671-674 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Pan X
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


66383 Assessment of Filtration Bleb and Endplate Positioning Using Magnetic Resonance Imaging in Eyes Implanted with Long-Tube Glaucoma Drainage Devices
Ohira A
PLoS ONE 2015; 10: e0144595 (IGR: 17-3)


66603 Saccadic vector optokinetic perimetry in children with neurodisability or isolated visual pathway lesions: observational cohort study
Dahlmann-Noor A
British Journal of Ophthalmology 2016; 100: 1427-1432 (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Li J
Scientific reports 2016; 6: 18969 (IGR: 17-3)


65903 Imaging mass spectrometry of the visual system: Advancing the molecular understanding of retina degenerations
Crouch RK
Proteomics - Clinical Applications 2016; 10: 391-402 (IGR: 17-3)


66251 Aqueous Angiography: Real-Time and Physiologic Aqueous Humor Outflow Imaging
Weinreb RN
PLoS ONE 2016; 11: e0147176 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Weber PA
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


65903 Imaging mass spectrometry of the visual system: Advancing the molecular understanding of retina degenerations
Schey KL
Proteomics - Clinical Applications 2016; 10: 391-402 (IGR: 17-3)


66550 Anterior chamber aqueous flare, pseudoexfoliation syndrome, and glaucoma
Jelliti B
International Ophthalmology 2016; 36: 671-674 (IGR: 17-3)


66251 Aqueous Angiography: Real-Time and Physiologic Aqueous Humor Outflow Imaging
Huang AS
PLoS ONE 2016; 11: e0147176 (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Xie X; Yang D
Scientific reports 2016; 6: 18969 (IGR: 17-3)


66550 Anterior chamber aqueous flare, pseudoexfoliation syndrome, and glaucoma
Khairallah M
International Ophthalmology 2016; 36: 671-674 (IGR: 17-3)


65903 Imaging mass spectrometry of the visual system: Advancing the molecular understanding of retina degenerations
Ablonczy Z
Proteomics - Clinical Applications 2016; 10: 391-402 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Hart RT
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Chen W
Scientific reports 2016; 6: 18969 (IGR: 17-3)


66616 Three-Dimensional Strains in Human Posterior Sclera Using Ultrasound Speckle Tracking
Liu J
Journal of Biomechanical Engineering 2016; 138: (IGR: 17-3)


66600 Structural brain alterations in primary open angle glaucoma: a 3T MRI study
Wang N; Xian J; He H
Scientific reports 2016; 6: 18969 (IGR: 17-3)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Huang X
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


60984 TH-CD-207-08: Neurodegeneration of the Visual Pathway in Mild Glaucoma Assessed by MRI
Zhou W
Medical Physics 2015; 42: 3736 (IGR: 17-1)


61702 Disturbed temporal dynamics of brain synchronization in vision loss
Bola M
Cortex; a journal devoted to the study of the nervous system and behavior 2015; 67: 134-146 (IGR: 17-1)


61696 Effect of topical anti-glaucoma medications on late pupillary light reflex, as evaluated by pupillometry
Ba-Ali S
Frontiers in neurology 2015; 6: 93 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Gerente VM
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61326 Biomechanical assessment in models of glaucomatous optic neuropathy
Nguyen TD
Experimental Eye Research 2015; 141: 125-138 (IGR: 17-1)


61331 Detection of asymmetric glaucomatous damage using automated pupillography, the swinging flashlight method and the magnified-assisted swinging flashlight method
Waisbourd M
Eye 2015; 29: 1321-1328 (IGR: 17-1)


61272 Functional Magnetic Resonance Imaging in Selected Eye Diseases
Lešták J
?eska a Slovenska Oftalmologie 2015; 71: 127-133 (IGR: 17-1)


61289 Advanced Morphological and Functional Magnetic Resonance Techniques in Glaucoma
Mastropasqua R
BioMed research international 2015; 2015: 160454 (IGR: 17-1)


61768 Cerebral glucose metabolism in the striate cortex positively correlates with fractional anisotropy values of the optic radiation in patients with glaucoma
Murai H
Clinical and Experimental Ophthalmology 2015; 43: 711-719 (IGR: 17-1)


61743 Change in corneal hysteresis over time in normal, glaucomatous and diabetic eyes
Hussnain SA
Acta Ophthalmologica 2015; 93: e627-e630 (IGR: 17-1)


61696 Effect of topical anti-glaucoma medications on late pupillary light reflex, as evaluated by pupillometry
Sander B
Frontiers in neurology 2015; 6: 93 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Schor RR
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61743 Change in corneal hysteresis over time in normal, glaucomatous and diabetic eyes
Alsberge JB
Acta Ophthalmologica 2015; 93: e627-e630 (IGR: 17-1)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Zhong YL
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


61272 Functional Magnetic Resonance Imaging in Selected Eye Diseases
Tintěra J
?eska a Slovenska Oftalmologie 2015; 71: 127-133 (IGR: 17-1)


60984 TH-CD-207-08: Neurodegeneration of the Visual Pathway in Mild Glaucoma Assessed by MRI
Muir E
Medical Physics 2015; 42: 3736 (IGR: 17-1)


61331 Detection of asymmetric glaucomatous damage using automated pupillography, the swinging flashlight method and the magnified-assisted swinging flashlight method
Lee B
Eye 2015; 29: 1321-1328 (IGR: 17-1)


61289 Advanced Morphological and Functional Magnetic Resonance Techniques in Glaucoma
Agnifili L
BioMed research international 2015; 2015: 160454 (IGR: 17-1)


61702 Disturbed temporal dynamics of brain synchronization in vision loss
Gall C
Cortex; a journal devoted to the study of the nervous system and behavior 2015; 67: 134-146 (IGR: 17-1)


61768 Cerebral glucose metabolism in the striate cortex positively correlates with fractional anisotropy values of the optic radiation in patients with glaucoma
Suzuki Y
Clinical and Experimental Ophthalmology 2015; 43: 711-719 (IGR: 17-1)


61326 Biomechanical assessment in models of glaucomatous optic neuropathy
Ethier CR
Experimental Eye Research 2015; 141: 125-138 (IGR: 17-1)


61289 Advanced Morphological and Functional Magnetic Resonance Techniques in Glaucoma
Mattei PA
BioMed research international 2015; 2015: 160454 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Chaim KT
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61696 Effect of topical anti-glaucoma medications on late pupillary light reflex, as evaluated by pupillometry
Brøndsted AE
Frontiers in neurology 2015; 6: 93 (IGR: 17-1)


61768 Cerebral glucose metabolism in the striate cortex positively correlates with fractional anisotropy values of the optic radiation in patients with glaucoma
Kiyosawa M
Clinical and Experimental Ophthalmology 2015; 43: 711-719 (IGR: 17-1)


61743 Change in corneal hysteresis over time in normal, glaucomatous and diabetic eyes
Ehrlich JR
Acta Ophthalmologica 2015; 93: e627-e630 (IGR: 17-1)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Zeng XJ
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


60984 TH-CD-207-08: Neurodegeneration of the Visual Pathway in Mild Glaucoma Assessed by MRI
Li W
Medical Physics 2015; 42: 3736 (IGR: 17-1)


61331 Detection of asymmetric glaucomatous damage using automated pupillography, the swinging flashlight method and the magnified-assisted swinging flashlight method
Ali MH
Eye 2015; 29: 1321-1328 (IGR: 17-1)


61702 Disturbed temporal dynamics of brain synchronization in vision loss
Sabel BA
Cortex; a journal devoted to the study of the nervous system and behavior 2015; 67: 134-146 (IGR: 17-1)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Zhou F
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


60984 TH-CD-207-08: Neurodegeneration of the Visual Pathway in Mild Glaucoma Assessed by MRI
Clarke G
Medical Physics 2015; 42: 3736 (IGR: 17-1)


61743 Change in corneal hysteresis over time in normal, glaucomatous and diabetic eyes
Shimmyo M
Acta Ophthalmologica 2015; 93: e627-e630 (IGR: 17-1)


61768 Cerebral glucose metabolism in the striate cortex positively correlates with fractional anisotropy values of the optic radiation in patients with glaucoma
Tokumaru AM
Clinical and Experimental Ophthalmology 2015; 43: 711-719 (IGR: 17-1)


61331 Detection of asymmetric glaucomatous damage using automated pupillography, the swinging flashlight method and the magnified-assisted swinging flashlight method
Lu L
Eye 2015; 29: 1321-1328 (IGR: 17-1)


61289 Advanced Morphological and Functional Magnetic Resonance Techniques in Glaucoma
Caulo M
BioMed research international 2015; 2015: 160454 (IGR: 17-1)


61696 Effect of topical anti-glaucoma medications on late pupillary light reflex, as evaluated by pupillometry
Lund-Andersen H
Frontiers in neurology 2015; 6: 93 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Felix Mde M
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61768 Cerebral glucose metabolism in the striate cortex positively correlates with fractional anisotropy values of the optic radiation in patients with glaucoma
Ishiwata K
Clinical and Experimental Ophthalmology 2015; 43: 711-719 (IGR: 17-1)


61289 Advanced Morphological and Functional Magnetic Resonance Techniques in Glaucoma
Fasanella V
BioMed research international 2015; 2015: 160454 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Ventura DF
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Liu XH
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


60984 TH-CD-207-08: Neurodegeneration of the Visual Pathway in Mild Glaucoma Assessed by MRI
Duong T
Medical Physics 2015; 42: 3736 (IGR: 17-1)


61743 Change in corneal hysteresis over time in normal, glaucomatous and diabetic eyes
Radcliffe NM
Acta Ophthalmologica 2015; 93: e627-e630 (IGR: 17-1)


61331 Detection of asymmetric glaucomatous damage using automated pupillography, the swinging flashlight method and the magnified-assisted swinging flashlight method
Martinez P; Faria B
Eye 2015; 29: 1321-1328 (IGR: 17-1)


61289 Advanced Morphological and Functional Magnetic Resonance Techniques in Glaucoma
Navarra R
BioMed research international 2015; 2015: 160454 (IGR: 17-1)


61768 Cerebral glucose metabolism in the striate cortex positively correlates with fractional anisotropy values of the optic radiation in patients with glaucoma
Ishii K
Clinical and Experimental Ophthalmology 2015; 43: 711-719 (IGR: 17-1)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Hu PH
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Teixeira SH
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61289 Advanced Morphological and Functional Magnetic Resonance Techniques in Glaucoma
Mastropasqua L
BioMed research international 2015; 2015: 160454 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Lottenberg CL
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61331 Detection of asymmetric glaucomatous damage using automated pupillography, the swinging flashlight method and the magnified-assisted swinging flashlight method
Williams A
Eye 2015; 29: 1321-1328 (IGR: 17-1)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Pei CG
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


61331 Detection of asymmetric glaucomatous damage using automated pupillography, the swinging flashlight method and the magnified-assisted swinging flashlight method
Moster MR
Eye 2015; 29: 1321-1328 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Amaro E
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Shao Y
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


61289 Advanced Morphological and Functional Magnetic Resonance Techniques in Glaucoma
Marchini G
BioMed research international 2015; 2015: 160454 (IGR: 17-1)


61486 Disturbed spontaneous brain activity pattern in patients with primary angle-closure glaucoma using amplitude of low-frequency fluctuation: a fMRI study
Dai XJ
Neuropsychiatric disease and treatment 2015; 11: 1877-1883 (IGR: 17-1)


61134 Evaluation of Glaucomatous Damage via Functional Magnetic Resonance Imaging, and Correlations Thereof with Anatomical and Psychophysical Ocular Findings
Paranhos A
PLoS ONE 2015; 10: e0126362 (IGR: 17-1)


61331 Detection of asymmetric glaucomatous damage using automated pupillography, the swinging flashlight method and the magnified-assisted swinging flashlight method
Katz LJ; Spaeth GL
Eye 2015; 29: 1321-1328 (IGR: 17-1)


60215 Open-angle glaucoma and paraoptic cyst: first description of a series of 11 patients
Bertrand A
American Journal of Neuroradiology 2015; 36: 779-782 (IGR: 16-4)


60143 Altered amplitude of low-frequency fluctuation in primary open-angle glaucoma: a resting-state FMRI study
Li T
Investigative Ophthalmology and Visual Science 2015; 56: 322-329 (IGR: 16-4)


60585 Ex-PRESS glaucoma filter: an MRI compatible metallic orbital foreign body imaged at 1.5 and 3T
Mabray MC
Clinical radiology 2015; 70: e28-e34 (IGR: 16-4)


60143 Altered amplitude of low-frequency fluctuation in primary open-angle glaucoma: a resting-state FMRI study
Liu Z
Investigative Ophthalmology and Visual Science 2015; 56: 322-329 (IGR: 16-4)


60215 Open-angle glaucoma and paraoptic cyst: first description of a series of 11 patients
Vignal C
American Journal of Neuroradiology 2015; 36: 779-782 (IGR: 16-4)


60585 Ex-PRESS glaucoma filter: an MRI compatible metallic orbital foreign body imaged at 1.5 and 3T
Uzelac A; Talbott JF
Clinical radiology 2015; 70: e28-e34 (IGR: 16-4)


60215 Open-angle glaucoma and paraoptic cyst: first description of a series of 11 patients
Lafitte F
American Journal of Neuroradiology 2015; 36: 779-782 (IGR: 16-4)


60143 Altered amplitude of low-frequency fluctuation in primary open-angle glaucoma: a resting-state FMRI study
Li J
Investigative Ophthalmology and Visual Science 2015; 56: 322-329 (IGR: 16-4)


60585 Ex-PRESS glaucoma filter: an MRI compatible metallic orbital foreign body imaged at 1.5 and 3T
Lin SC
Clinical radiology 2015; 70: e28-e34 (IGR: 16-4)


60215 Open-angle glaucoma and paraoptic cyst: first description of a series of 11 patients
Koskas P
American Journal of Neuroradiology 2015; 36: 779-782 (IGR: 16-4)


60143 Altered amplitude of low-frequency fluctuation in primary open-angle glaucoma: a resting-state FMRI study
Tang Z
Investigative Ophthalmology and Visual Science 2015; 56: 322-329 (IGR: 16-4)


60215 Open-angle glaucoma and paraoptic cyst: first description of a series of 11 patients
Bergès O
American Journal of Neuroradiology 2015; 36: 779-782 (IGR: 16-4)


60585 Ex-PRESS glaucoma filter: an MRI compatible metallic orbital foreign body imaged at 1.5 and 3T
Gean AD
Clinical radiology 2015; 70: e28-e34 (IGR: 16-4)


60143 Altered amplitude of low-frequency fluctuation in primary open-angle glaucoma: a resting-state FMRI study
Xie X
Investigative Ophthalmology and Visual Science 2015; 56: 322-329 (IGR: 16-4)


60215 Open-angle glaucoma and paraoptic cyst: first description of a series of 11 patients
Héran F
American Journal of Neuroradiology 2015; 36: 779-782 (IGR: 16-4)


60143 Altered amplitude of low-frequency fluctuation in primary open-angle glaucoma: a resting-state FMRI study
Yang D; Wang N; Tian J; Xian J
Investigative Ophthalmology and Visual Science 2015; 56: 322-329 (IGR: 16-4)


58903 Magic angle-enhanced MRI of fibrous microstructures in sclera and cornea with and without intraocular pressure loading
Ho LC; Sigal IA; Jan NJ; Squires A; Tse Z; Wu EX; Kim SG; Schuman JS; Chan KC
Investigative Ophthalmology and Visual Science 2014; 55: 5662-5672 (IGR: 16-3)


59267 Cerebral Microinfarcts in Primary Open-Angle Glaucoma Correlated With DTI-Derived Integrity of Optic Radiation
Schoemann J; Engelhorn T; Waerntges S; Doerfler A; El-Rafei A; Michelson G
Investigative Ophthalmology and Visual Science 2014; 55: 7241-7247 (IGR: 16-3)


59284 A combined method to quantify the retinal metabolic rate of oxygen using photoacoustic ophthalmoscopy and optical coherence tomography
Song W; Wei Q; Liu W; Liu T; Yi J; Sheibani N; Fawzi AA; Linsenmeier RA; Jiao S; Zhang HF
Scientific reports 2014; 4: 6525 (IGR: 16-3)


58777 Relationship between visual acuity and retinal structures measured by spectral domain optical coherence tomography in patients with open-angle glaucoma
Kim JH; Lee HS; Kim NR; Seong GJ; Kim CY
Investigative Ophthalmology and Visual Science 2014; 55: 4801-4811 (IGR: 16-3)


59079 Morphologic changes in the anterior and posterior subregions of V1 and V2 and the V5/MT+ in patients with primary open-angle glaucoma
Yu L; Yin X; Dai C; Liang M; Wei L; Li C; Zhang J; Xie B; Wang J
Brain Research 2014; 1588: 135-143 (IGR: 16-3)


58774 Glaucomatous and age-related changes in corneal pulsation shape. The ocular dicrotism
Danielewska ME; Krzyżanowska-Berkowska P; Iskander DR
PLoS ONE 2014; 9: e102814 (IGR: 16-3)


57078 In vivo assessment of aqueous humor dynamics upon chronic ocular hypertension and hypotensive drug treatment using gadolinium-enhanced MRI
Ho LC; Conner IP; Do CW; Kim SG; Wu EX; Wollstein G; Schuman JS; Chan KC
Investigative Ophthalmology and Visual Science 2014; 55: 3747-3757 (IGR: 16-2)


57093 Novel use of 3T MRI in assessment of optic nerve volume in glaucoma
Ramli NM; Sidek S; Rahman FA; Peyman M; Zahari M; Rahmat K; Ramli N
Graefe's Archive for Clinical and Experimental Ophthalmology 2014; 252: 995-1000 (IGR: 16-2)


57026 An investigation of lateral geniculate nucleus volume in patients with primary open-angle glaucoma using 7 tesla magnetic resonance imaging
Lee JY; Jeong HJ; Lee JH; Kim YJ; Kim EY; Kim YY; Ryu T; Cho ZH; Kim YB
Investigative Ophthalmology and Visual Science 2014; 55: 3468-3476 (IGR: 16-2)


57422 Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images
Ramaswamy G; Lombardo M; Devaney N
Biomedical optics express 2014; 5: 1941-1951 (IGR: 16-2)


57362 Glaucoma severity affects diffusion tensor imaging (DTI) parameters of the optic nerve and optic radiation
Sidek S; Ramli N; Rahmat K; Ramli NM; Abdulrahman F; Tan LK
European journal of radiology 2014; 83: 1437-1441 (IGR: 16-2)


56665 DTI Analysis in Patients with Primary Open-Angle Glaucoma: Impact of Registration on Voxel-Wise Statistics
Schmidt MA; Mennecke A; Michelson G; Doerfler A; Engelhorn T
PLoS ONE 2014; 9: e99344 (IGR: 16-1)


56237 Vision restoration training for glaucoma: a randomized clinical trial
Sabel BA; Gudlin J
JAMA ophthalmology 2014; 132: 381-389 (IGR: 16-1)


56219 Detecting glaucoma using automated pupillography
Tatham AJ; Meira-Freitas D; Weinreb RN; Zangwill LM; Medeiros FA
Ophthalmology 2014; 121: 1185-1193 (IGR: 16-1)


55681 Altered spontaneous brain activity in primary open angle glaucoma: a resting-state functional magnetic resonance imaging study
Song Y; Mu K; Wang J; Lin F; Chen Z; Yan X; Hao Y; Zhu W; Zhang H
PLoS ONE 2014; 9: e89493 (IGR: 15-4)


55270 Anterior Segment Applications of In Vivo Confocal Microscopy
Kymionis GD; Diakonis VF; Shehadeh MM; Pallikaris AI; Pallikaris IG
Seminars in Ophthalmology 2015; 30: 243-251 (IGR: 15-4)


55780 Alteration of fractional anisotropy and mean diffusivity in glaucoma: novel results of a meta-analysis of diffusion tensor imaging studies
Li K; Lu C; Huang Y; Yuan L; Zeng D; Wu K
PLoS ONE 2014; 9: e97445 (IGR: 15-4)


55735 Strategies for improving early detection of glaucoma: the combined structure-function index
Tatham AJ; Weinreb RN; Medeiros FA
Clinical Ophthalmology 2014; 8: 611-621 (IGR: 15-4)


55670 The application and research progress of functional magnetic resonance imaging in glaucoma
Yang HF; Liu TT; Sun XH
Chinese Journal of Ophthalmology 2013; 49: 1040-1044 (IGR: 15-4)


54826 Correlation of Magnetic Resonance Imaging optic nerve parameters to Optical Coherence Tomography and the visual field in glaucoma
Omodaka K; Murata T; Sato S; Takahashi M; Tatewaki Y; Nagasaka T; Doi H; Araie M; Takahashi S; Nakazawa T
Clinical and Experimental Ophthalmology 2014; 42: 360-368 (IGR: 15-3)


54694 Reduced cortical thickness in primary open-angle glaucoma and its relationship to the retinal nerve fiber layer thickness
Yu L; Xie B; Yin X; Liang M; Evans AC; Wang J; Dai C
PLoS ONE 2013; 8: e73208 (IGR: 15-3)


54421 Evidence for widespread structural brain changes in glaucoma: a preliminary voxel-based MRI study
Williams AL; Lackey J; Wizov SS; Chia TM; Gatla S; Moster ML; Sergott R; Spaeth GL; Lai S
Investigative Ophthalmology and Visual Science 2013; 54: 5880-5887 (IGR: 15-3)


54680 Proton magnetic resonance spectroscopy ((1)H-MRS) reveals geniculocalcarine and striate area degeneration in primary glaucoma
Zhang Y; Chen X; Wen G; Wu G; Zhang X
PLoS ONE 2013; 8: e73197 (IGR: 15-3)


54805 Correlation between peripapillary retinal nerve fiber layer thickness and fundus autofluorescence in primary open-angle glaucoma
Reznicek L; Seidensticker F; Mann T; Hü,bert I; Buerger A; Haritoglou C; Neubauer AS; Kampik A; Hirneiss C; Kernt M
Clinical Ophthalmology 2013; 7: 1883-1888 (IGR: 15-3)


54401 Reading performance in patients with glaucoma evaluated using the MNREAD charts
Ishii M; Seki M; Harigai R; Abe H; Fukuchi T
Japanese Journal of Ophthalmology 2013; 57: 471-474 (IGR: 15-3)


54764 Pupillographic evaluation of relative afferent pupillary defect in glaucoma patients
Ozeki N; Yuki K; Shiba D; Tsubota K
British Journal of Ophthalmology 2013; 97: 1538-1542 (IGR: 15-3)


54683 Development and validation of an associative model for the detection of glaucoma using pupillography
Chang DS; Arora KS; Boland MV; Supakontanasan W; Friedman DS
American Journal of Ophthalmology 2013; 156: 1285-1296 (IGR: 15-3)


53843 In vivo evaluation of lamina cribrosa deformation in glaucoma
Park SC
Journal of Glaucoma 2013; 22: S29-31 (IGR: 15-2)


53842 How to measure cerebrospinal fluid pressure invasively and noninvasively
Silverman CA; Linstrom CJ
Journal of Glaucoma 2013; 22: S26-8 (IGR: 15-2)


53889 Glaucoma classification based on visual pathway analysis using diffusion tensor imaging
El-Rafei A; Engelhorn T; Wärntges S; Dörfler A; Hornegger J; Michelson G
Magnetic Resonance Imaging 2013; 31: 1081-1091 (IGR: 15-2)


53840 Imaging visual cortical structure and function in vivo
Majewska AK
Journal of Glaucoma 2013; 22: S21-3 (IGR: 15-2)


54000 Accuracy of Pupil Assessment for the Detection of Glaucoma: A Systematic Review and Meta-analysis
Chang DS; Xu L; Boland MV; Friedman DS
Ophthalmology 2013; 120: 2217-2225 (IGR: 15-2)


53797 Magnetic resonance imaging of the retina: From mice to men
Duong TQ
Magnetic resonance in medicine 2014; 71: 1526-1530 (IGR: 15-2)


53846 Noninvasive brain stimulation in the study of the human visual system
Halko MA; Eldaief MC; Pascual-Leone A
Journal of Glaucoma 2013; 22: S39-41 (IGR: 15-2)


53782 Thermography: A New Option to Monitor Filtering Bleb Function?
Klamann MK; Maier AK; Gonnermann J; Klein JP; Ruokonen P; Pleyer U
Journal of Glaucoma 2015; 24: 272-277 (IGR: 15-2)


53654 Optic Nerve Diffusion Tensor Imaging Parameters and Their Correlation With Optic Disc Topography and Disease Severity in Adult Glaucoma Patients and Controls
Chang ST; Xu J; Trinkaus K; Pekmezci M; Arthur SN; Song SK; Barnett EM
Journal of Glaucoma 2014; 23: 513-520 (IGR: 15-2)


53852 Glaucoma and CNS. Comparison of fMRI results in high tension and normal tension glaucoma
Lestak J; Tintera J; Svata Z; Ettler L; Rozsival P
Biomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia 2014; 158: 144-153 (IGR: 15-2)


52091 Anterior segment examination in paediatric patients: the closed probe system
Simonini VM; Lodi L
Acta Clinica Croatica 2012; 51: 45-50 (IGR: 14-4)


51695 Balance control in glaucoma
Kotecha A; Richardson G; Chopra R; Fahy RT; Garway-Heath DF; Rubin GS
Investigative Ophthalmology and Visual Science 2012; 53: 7795-7801 (IGR: 14-4)


51670 Phosphene thresholds elicited by transcorneal electrical stimulation in healthy subjects and patients with retinal diseases
Naycheva L; Schatz A; Röck T; Willmann G; Messias A; Bartz-Schmidt KU; Zrenner E; Gekeler F
Investigative Ophthalmology and Visual Science 2012; 53: 7440-7448 (IGR: 14-4)


52038 Functional magnetic resonance imaging in glaucoma
Chen ZQ; Gao J; Zhang H
Chinese Journal of Ophthalmology 2012; 48: 1045-1048 (IGR: 14-4)


50971 Reduced white matter integrity in primary open-angle glaucoma: A DTI study using tract-based spatial statistics
Lu P; Shi L; Du H; Xie B; Li C; Li S; Liu T; Feng H; Wang J
Journal of neuroradiology. Journal de neuroradiologie 2013; 40: 89-93 (IGR: 14-3)


50888 Impact of repeated topical-loaded manganese-enhanced MRI on the mouse visual system
Sun SW; Thiel T; Liang HF
Investigative Ophthalmology and Visual Science 2012; 53: 4699-4709 (IGR: 14-3)


51172 Clinical applications of high-resolution ocular magnetic resonance imaging
Tanitame K; Sone T; Kiuchi Y; Awai K
Japanese journal of radiology 2012; 30: 695-705 (IGR: 14-3)


51183 In vivo analysis of vectors involved in pupil constriction in Chinese subjects with angle closure
Zheng C; Cheung CY; Aung T; Narayanaswamy A; Ong SH; Friedman DS; Allen JC; Baskaran M; Chew PT; Perera SA
Investigative Ophthalmology and Visual Science 2012; 53: 6756-6762 (IGR: 14-3)


51375 Oxidative stress in the closed-eyelid test: management of glaucoma
Pescosolido N; Malagola R; Scarsella G; Lenarduzzi F; Dapoto L; Nebbioso M
European review for medical and pharmacological sciences 2012; 16: 1453-1457 (IGR: 14-3)


50756 Visual symptoms and retinal straylight after laser peripheral iridotomy: the Zhongshan Angle-Closure Prevention Trial
Congdon N; Yan X; Friedman DS; Foster PJ; van den Berg TJ; Peng M; Gangwani R; He M
Ophthalmology 2012; 119: 1375-1382 (IGR: 14-3)


50442 Voxel-based Morphometry of the Visual-related Cortex in Primary Open Angle Glaucoma
Li C; Cai P; Shi L; Lin Y; Zhang J; Liu S; Xie B; Shi Y; Yang H; Li S; Du H; Wang J
Current Eye Research 2012; 37: 794-802 (IGR: 14-2)


50438 Evaluation of corpus geniculatum laterale and vitreous fluid by magnetic resonance spectroscopy in patients with glaucoma; a preliminary study
Doganay S; Cankaya C; Alkan A
Eye 2012; 26: 1044-1051 (IGR: 14-2)


50390 Changes of radial diffusivity and fractional anisotopy in the optic nerve and optic radiation of glaucoma patients
Engelhorn T; Michelson G; Waerntges S; Otto M; El-Rafei A; Struffert T; Doerfler A
TheScientificWorldJournal 2012; 2012: 849632 (IGR: 14-2)


50439 3-T Diffusion tensor imaging of the optic nerve in subjects with glaucoma: correlation with GDx-VCC, HRT-III and Stratus optical coherence tomography findings
Nucci C; Mancino R; Martucci A; Bolacchi F; Manenti G; Cedrone C; Culasso F; Floris R; Cerulli L; Garaci FG
British Journal of Ophthalmology 2012; 96: 976-980 (IGR: 14-2)


50355 Differences between Proximal versus Distal Intraorbital Optic Nerve Diffusion Tensor Magnetic Resonance Imaging Properties in Glaucoma Patients
Bolacchi F; Garaci FG; Martucci A; Meschini A; Fornari M; Marziali S; Mancino R; Squillaci E; Floris R; Cerulli L; Simonetti G; Nucci C
Investigative Ophthalmology and Visual Science 2012; 53: 4191-4196 (IGR: 14-2)


50562 Diffusion tensor MRI reveals visual pathway damage that correlates with clinical severity in glaucoma
Chen Z; Lin F; Wang J; Li Z; Dai H; Mu K; Ge J; Zhang H
Clinical and Experimental Ophthalmology 2013; 41: 43-49 (IGR: 14-2)


46592 Diagnostic value of macular morphometry in patients with primary open-angle glaucoma
Mamikonian VR; Kazarian EE; Galoian NS; Kozlova IV; Shmeleva-Demir OA; Mazurova IV; Basaeva EA
Vestnik Oftalmologii 2010; 126: 8-12 (IGR: 13-3)


45898 Practical significance of critical fusion frequency (CFF): Chronological resolution of the visual system in differential diagnosis
Baatz H; Raak P; De Ortueta D; Mirshahi A; Scharioth G
Ophthalmologe 2010; 107: 715-719 (IGR: 13-2)


45564 The post-illumination pupil response is reduced in glaucoma patients
Kankipati L; Girkin CA; Gamlin PD
Investigative Ophthalmology and Visual Science 2011; 52: 2287-2292 (IGR: 13-2)


46308 Comparison of stereo disc photographs and alternation flicker using a novel matching technology for detecting glaucoma progression
Radcliffe NM; Sehi M; Wallace IB; Greenfield DS; Krupin T; Ritch R
Ophthalmic surgery, lasers & imaging : the official journal of the International Society for Imaging in the Eye 2010; 41: 629-634 (IGR: 13-2)


46106 Evaluation of the relationship between quality of vision and visual function in Japanese glaucoma patients
Sawada H; Fukuchi T; Abe H
Clinical Ophthalmology 2011; 5: 259-267 (IGR: 13-2)


27849 The utility of relative afferent pupillary defect as a screening tool for glaucoma: Prospective examination of a large population-based study in a south Indian population
Hennessy AL; Katz J; Ramakrishnan R; Krishnadas R; Thulasiraj RD; Tielsch JM; Robin AL
British Journal of Ophthalmology 2011; (IGR: 13-1)


27804 Hemispherical focal macular photopic negative response and macular inner retinal thickness in open-angle glaucoma
Nakamura H; Hangai M; Mori S; Hirose F; Yoshimura N
American Journal of Ophthalmology 2011; 151: 494-506 (IGR: 13-1)


26517 Patterns of colour vision loss in patients with retinal and optic nerve disease
Rodriguez-Carmona M; O'Neill-Biba M; Barbur JL
Neuro-Ophthalmology 2010; 34: 139-140 (IGR: 12-3)


26354 Fundus autofluorescence and spectral-domain optical coherence tomography findings of leopard spots in nanophthalmic uveal effusion syndrome
Okuda T; Higashide T; Wakabayashi Y; Nishimura A; Sugiyama K
Graefe's Archive for Clinical and Experimental Ophthalmology 2010; 248: 1199-1202 (IGR: 12-3)


26075 Combining Functional and Structural Tests Improves the Diagnostic Accuracy of Relevance Vector Machine Classifiers
Racette L; Chiou CY; Hao J; Bowd C; Goldbaum MH; Zangwill LM; Lee TW; Weinreb RN; Sample PA
Journal of Glaucoma 2010; 19: 167-175 (IGR: 12-2)


25821 Optimal fast T2-weighted magnetic resonance microscopy imaging of the eye and its clinical application
Tanitame K; Sasaki K; Sone T; Otani K
Journal of Magnetic Resonance Imaging 2010; 31: 1210-1214 (IGR: 12-2)


25467 Clinical evaluation of a rapid, pupil-based assessment of retinal damage associated with glaucoma
Wride N; Habib M; Morris K; Campbell S; Fraser S
Clinical Ophthalmology 2009; 3: 123-128 (IGR: 12-1)


25346 High resolution three-dimensional reconstruction of the collagenous matrix of the human optic nerve head
Winkler M; Jester B; Nien-Shy C; Massei S; Minckler D S; Jester J V; Brown D J
Brain Research Bulletin 2010; 81: 339-348 (IGR: 12-1)


25261 Conventional MRI and magnetisation transfer imaging of the brain and optic pathway in primary open-angle glaucoma
Kitsos G; Zikou A K; Bagli E; Kosta P; Argyropoulou M I
British Journal of Radiology 2009; 82: 983: 896-900 (IGR: 12-1)


25154 Distribution and determinants of ocular biometric parameters in an Asian population: the Singapore Malay eye study
Lim LS; Saw SM; Jeganathan VS; Tay WT; Aung T; Tong L; Mitchell P; Wong TY
Investigative Ophthalmology and Visual Science 2010; 51: 103-109 (IGR: 12-1)


25473 Acquired color vision and visual field defects in patients with ocular hypertension and early glaucoma
Papaconstantinou D; Georgalas I; Kalantzis G; Karmiris E; Koutsandrea C; Diagourtas A; Ladas I; Georgopoulos G
Clinical Ophthalmology 2009; 3: 251-257 (IGR: 12-1)


25327 Is the flashlight test of any use in primary care for detecting eyes with shallow anterior chamber?
Trueba Castillo A; Negredo Bravo L J; Cardenas Valencia C; Gil De Gomez Barragan M J; Arribas Garcia R A
Atencion Primaria 2010; 42: 149-153 (IGR: 12-1)


25190 Fixation behavior in advanced stage glaucoma assessed by the MicroPerimeter MP-1
Kameda T; Tanabe T; Hangai M; Ojima T; Aikawa H; Yoshimura N
Japanese Journal of Ophthalmology 2009; 53: 580-587 (IGR: 12-1)


25031 Impairments of contrast discrimination and contrast adaptation in glaucoma
McKendrick AM; Sampson GP; Walland MJ; Badcock DR
Investigative Ophthalmology and Visual Science 2010; 51: 920-927 (IGR: 12-1)


24918 Functional imaging using the retinal function imager: direct imaging of blood velocity, achieving fluorescein angiography-like images without any contrast agent, qualitative oximetry, and functional metabolic signals
Izhaky D; Nelson DA; Burgansky-Eliash Z; Grinvald A
Japanese Journal of Ophthalmology 2009; 53: 345-351 (IGR: 11-4)


24685 In-vivo imaging of retinal nerve fiber layer vasculature: imaging histology comparison
Scoles D; Gray DC; Hunter JJ; Wolfe R; Gee BP; Geng Y; Masella BD; Libby RT; Russell S; Williams DR
BMC Ophthalmology 2009; 9: 9 (IGR: 11-4)


24701 High-resolution ocular imaging: combining advanced optics and microtechnology
Cordeiro MF; Nickells R; Drexler W; Borras T; Ritch R
Ophthalmic Surgery Lasers and Imaging 2009; 40: 480-488 (IGR: 11-4)


24703 Early diagnosis of ocular hypertension using a low-intensity laser irradiation test
Ivandic BT; Hoque NN; Ivandic T
Photomedicine and Laser Surgery 2009; 27: 571-575 (IGR: 11-4)


24162 Retrobulbar optic nerve diameter measured by high-speed magnetic resonance imaging as a biomarker for axonal loss in glaucomatous optic atrophy
LagrŔze WA; Gaggl M; Weigel M; Schulte-M÷nting J; BŘhler A; Bach M; Munk RD; Bley TA
Investigative Ophthalmology and Visual Science 2009; 50: 4223-4228 (IGR: 11-3)


23603 Dynamic contrast-enhanced MRI of ocular biotransport in normal and hypertensive eyes
Chan KC; Fu QL; So KF; Wu EX
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2008; 2008:- 835-838 (IGR: 11-2)


22737 Spatial alignment over retinal scotomas
Crossland MD; Bex PJ
Investigative Ophthalmology and Visual Science 2009; 50: 1464-1469 (IGR: 11-1)


21694 Conjunctival modifications in ocular hypertension and primary open angle glaucoma: an in vivo confocal microscopy study
Ciancaglini M; Carpineto P; Agnifili L; Nubile M; Fasanella V; Mastropasqua L
Investigative Ophthalmology and Visual Science 2008; 49: 3042-3048 (IGR: 10-3)


21677 Filtering bleb functionality: a clinical, anterior segment optical coherence tomography and in vivo confocal microscopy study
Ciancaglini M; Carpineto P; Agnifili L; Nubile M; Lanzini M; Fasanella V; Mastropasqua L
Journal of Glaucoma 2008; 17: 308-317 (IGR: 10-3)


21153 Evaluation of the retina and optic nerve in a rat model of chronic glaucoma using in vivo manganese-enhanced magnetic resonance imaging
Chan KC; Fu Q-L; Hui ES; So K-F; Wu EX
Neuroimage 2008; 40: 1166-1174 (IGR: 10-2)


20979 Cerebrospinal fluid pressure is decreased in primary open-angle glaucoma
Berdahl JP; Allingham RR; Johnson DH
Ophthalmology 2008; 115: 763-768 (IGR: 10-2)


21234 Evaluation of the visual system in a rat model of chronic glaucoma using manganese-enhanced magnetic resonance imaging
Chan KC; Fu QL; So KF; Wu EX
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2007; 2007: 67-70 (IGR: 10-2)


21110 Study of MR imaging of optic nerve in the case with complication of disc anomaly and normal tension glaucoma
Nakao Y
Neuro-Ophthalmology Japan 2007; 24: 397-404 (IGR: 10-2)


20882 Comparison of the pupillometry during videonystagmography in asymmetric pseudoexfoliation patients
YŘlek F; Konukseven OO; Cakmak HB; Orhan N; Sim?ek S; Kutluhan A
Current Eye Research 2008; 33: 263-267 (IGR: 10-2)


15259 Assessment of axonal degeneration along the human visual pathway using diffusion trace analysis
Ueki S; Fujii Y; Matsuzawa H; Takagi M; Abe H; Kwee IL; Nakada T
American Journal of Ophthalmology 2006; 142: 591-596 (IGR: 8-4)


14792 Effects of retinal image degradation on preattentive visual search (PAVS) efficiency for flicker, movement and orientation stimuli
Davison P; Loughman J
Ophthalmic and Physiological Optics 2006; 26: 456-463 (IGR: 8-4)


15145 Pupillographic measurements with pattern stimulation: the pupil's response in normal subjects and first measurements in glaucoma patients
Link B; Junemann A; Rix R; Sembritzki O; Brenning A; Korth M; Horn FK
Investigative Ophthalmology and Visual Science 2006; 47: 4947-4955 (IGR: 8-4)


13981 In vivo confocal microscopy of filtering blebs after trabeculectomy
Messmer EM; Zapp DM; Mackert MJ; Thiel M; Kampik A
Archives of Ophthalmology 2006; 124: 1095-1103 (IGR: 8-3)


14095 Three-dimensional confocal laser scanning microscopy of the corneal nerve structure
Stachs O; Knappe S; Zhivov A; Kraak R; Stave J; Guthoff RF
Klinische Monatsblńtter fŘr Augenheilkunde 2006; 223: 583-588 (IGR: 8-3)


13850 Intravascular oxygen saturation in retinal vessels in normal subjects and open-angle glaucoma subjects
Michelson G; Scibor M
Acta Ophthalmologica Scandinavica 2006; 84: 289-295 (IGR: 8-2)


13638 An objective method for measuring relative afferent pupillary defect in glaucomatous optic neuropathy-stimulus optimization
Kalaboukhova L; Fridhammar V; Lindblom B
Neuro-Ophthalmology 2006; 30: 7-15 (IGR: 8-2)


13492 Measuring intraocular pressure-adjustments for corneal thickness and new technologies
Herndon LW
Current Opinions in Ophthalmology 2006; 17: 115-119 (IGR: 8-1)


13536 Magnetic resonance imaging of the brain in patients with pseudoexfoliation syndrome and glaucoma
Yuksel N; Anik Y; Altintas O; Onur I; Caglar Y; Demirci A
Ophthalmologica 2006; 220: 125-130 (IGR: 8-1)


12673 The re-engineering of a software system for glaucoma analysis
Fraser RG; Armarego J; Yogesan K
Computer Methods and Programs in Biomedicine 2005; 79: 97-109 (IGR: 7-3)


13069 Optical coherence tomography machine learning classifiers for glaucoma detection: a preliminary study
Burgansky-Eliash Z; Wollstein G; Chu T; Ramsey JD; Glymour C; Noecker RJ; Ishikawa H; Schuman JS
Investigative Ophthalmology and Visual Science 2005; 46: 4147-4152 (IGR: 7-3)


13179 Development and comparison of automated classifiers for glaucoma diagnosis using Stratus optical coherence tomography
Huang ML; Chen HY
Investigative Ophthalmology and Visual Science 2005; 46: 4121-4129 (IGR: 7-3)


12994 Predictive value of colour Doppler imaging in a prospective study of visual field progression in primary open-angle glaucoma
Martinez A; Sanchez M
Acta Ophthalmologica Scandinavica 2005; 83: 716-722 (IGR: 7-3)


13171 Effects of input data on the performance of a neural network in distinguishing normal and glaucomatous visual fields
Bengtsson B; Bizios D; Heijl A
Investigative Ophthalmology and Visual Science 2005; 46: 3730-3376 (IGR: 7-3)


13164 Using unsupervised learning with independent component analysis to identify patterns of glaucomatous visual field defects
Goldbaum MH; Sample PA; Zhang Z; Chan K; Hao J; Lee TW; Boden C; Bowd C; Bourne R; Zangwill L
Investigative Ophthalmology and Visual Science 2005; 46: 3676-3683 (IGR: 7-3)


13150 Episcleral venous pressure in untreated primary open-angle and normal-tension glaucoma
Selbach JM; Posielek K; Steuhl KP; Kremmer S
Ophthalmologica 2005; 219: 357-361 (IGR: 7-3)


12397 Random measurement error in visual acuity measurement in clinical settings
Leinonen J; Laakkonen E; Laatikainen L
Acta Ophthalmologica Scandinavica 2005; 83: 328-332 (IGR: 7-2)



2.13 Retina and retinal nerve fibre layer (4465 abstracts found)


85222 Assessment of primary open-angle glaucoma peripapillary and macular choroidal area using enhanced depth imaging optical coherence tomography
Kojima H
PLoS ONE 2020; 15: e0231214 (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Hou H
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Lee K
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


85179 Offline computer-aided diagnosis for Glaucoma detection using fundus images targeted at mobile devices
Martins J
Computer Methods and Programs in Biomedicine 2020; 192: 105341 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Dervenis N
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84842 Comparison of glaucoma diagnostic ability of ganglion cell-inner plexiform layer according to the range around the fovea
Jung JH
BMC Ophthalmology 2019; 19: 270 (IGR: 21-1)


85051 Vps35 Deficiency Impairs Cdk5/p35 Degradation and Promotes the Hyperphosphorylation of Tau Protein in Retinal Ganglion Cells
Gao L
Investigative Ophthalmology and Visual Science 2020; 61: 1 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Ha A
Scientific reports 2019; 9: 19771 (IGR: 21-1)


84526 Ganglion Cell-Inner Plexiform Layer and Retinal Nerve Fiber Layer Changes in Glaucoma Suspects Enable Prediction of Glaucoma Development
Shin JW
American Journal of Ophthalmology 2020; 210: 26-34 (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Hirooka K
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


84649 Localized Retinal Nerve Fiber Layer Defect Location Among Red-free Fundus Photographs, En Face Structural Images, and Cirrus HD-OCT Maps
Park JH
Journal of Glaucoma 2019; 28: 1054-1060 (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Hou H
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Uchida A
Scientific reports 2020; 10: 779 (IGR: 21-1)


84900 Temporal Wedge Defects in Glaucoma: Structure / Function Correlation with Threshold Automated Perimetry of the Full Visual Field
Wall M
Journal of Glaucoma 2020; 0: (IGR: 21-1)


84293 Correlating Structural and Functional Damage in Glaucoma
Torres LA
Journal of Glaucoma 2019; 28: 1079-1085 (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Wang AY
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84536 Retinal nerve fibre layer thickness in a normal black South African population
Ismail S
Eye 2019; 0: (IGR: 21-1)


85148 Ganglion Cell Complex Analysis in Glaucoma Patients: What Can It Tell Us?
Scuderi G
Eye and brain 2020; 12: 33-44 (IGR: 21-1)


84813 Risk factors associated with progressive nerve fiber layer thinning in open-angle glaucoma with mean intraocular pressure below 15 mmHg
Lee JS
Scientific reports 2019; 9: 19811 (IGR: 21-1)


84510 Intravitreal S100B Injection Triggers a Time-Dependent Microglia Response in a Pro-Inflammatory Manner in Retina and Optic Nerve
Grotegut P
Molecular Neurobiology 2020; 57: 1186-1202 (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Hou H
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Yang H
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84696 Estimating Visual Field Mean Deviation using Optical Coherence Tomographic Nerve Fiber Layer Measurements in Glaucoma Patients
Tan O
Scientific reports 2019; 9: 18528 (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
King BJ
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


85222 Assessment of primary open-angle glaucoma peripapillary and macular choroidal area using enhanced depth imaging optical coherence tomography
Kojima H
PLoS ONE 2020; 15: e0231214 (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Wang AY
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84978 Comparisons of ganglion cell-inner plexiform layer loss patterns and its diagnostic performance between normal tension glaucoma and primary open angle glaucoma: a detailed, severity-based study
Xu XY
International Journal of Ophthalmology 2020; 13: 71-78 (IGR: 21-1)


84822 Evaluation of Papillomacular Nerve Fiber Bundle Thickness in Glaucoma Patients with Visual Acuity Disturbance
Takahashi N
Current Eye Research 2019; 0: 1-7 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Tribble JR
Brain communications 2019; 1: fcz035 (IGR: 21-1)


84766 Peripapillary Vessel Density in Young Patients with Open-Angle Glaucoma: Comparison between High-Tension and Normal-Tension Glaucoma
Park JH
Scientific reports 2019; 9: 19160 (IGR: 21-1)


85159 Pathogenic roles of retinal glia in glaucoma
Shinozaki Y
Nippon yakurigaku zasshi 2020; 155: 87-92 (IGR: 21-1)


84830 Elevated intraocular pressure induces neuron-specific β-III-tubulin expression in non-neuronal vascular cells
Prokosch V
Acta Ophthalmologica 2019; 0: (IGR: 21-1)


84896 Macular vessel density versus ganglion cell complex thickness for detection of early primary open-angle glaucoma
Wang Y
BMC Ophthalmology 2020; 20: 17 (IGR: 21-1)


85025 A neuroglia-based interpretation of glaucomatous neuroretinal rim thinning in the optic nerve head
Lee EJ
Progress in Retinal and Eye Research 2020; 0: 100840 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Ocansey S
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


85158 Expression changes in microRNA in the retina of retinal degenerative diseases
Sakamoto K
Nippon yakurigaku zasshi 2020; 155: 81-86 (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Chen A
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Zheng C
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


84988 Accuracy of the ISNT rule and its variants for differentiating glaucomatous from normal eyes in a population-based study
Maupin E
British Journal of Ophthalmology 2020; 0: (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Liu L
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


84897 Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images
Lim AB
BMC Ophthalmology 2020; 20: 16 (IGR: 21-1)


85210 The Role of Autophagy in Glaucomatous Optic Neuropathy
Adornetto A
Frontiers in cell and developmental biology 2020; 8: 121 (IGR: 21-1)


84842 Comparison of glaucoma diagnostic ability of ganglion cell-inner plexiform layer according to the range around the fovea
Seo JH
BMC Ophthalmology 2019; 19: 270 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Abu EK
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84766 Peripapillary Vessel Density in Young Patients with Open-Angle Glaucoma: Comparison between High-Tension and Normal-Tension Glaucoma
Yoo C
Scientific reports 2019; 9: 19160 (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Xie X
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


84900 Temporal Wedge Defects in Glaucoma: Structure / Function Correlation with Threshold Automated Perimetry of the Full Visual Field
Lee EJ
Journal of Glaucoma 2020; 0: (IGR: 21-1)


84813 Risk factors associated with progressive nerve fiber layer thinning in open-angle glaucoma with mean intraocular pressure below 15 mmHg
Seong GJ
Scientific reports 2019; 9: 19811 (IGR: 21-1)


85222 Assessment of primary open-angle glaucoma peripapillary and macular choroidal area using enhanced depth imaging optical coherence tomography
Hirooka K
PLoS ONE 2020; 15: e0231214 (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Lee PY
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Sun S
Scientific reports 2019; 9: 19771 (IGR: 21-1)


84978 Comparisons of ganglion cell-inner plexiform layer loss patterns and its diagnostic performance between normal tension glaucoma and primary open angle glaucoma: a detailed, severity-based study
Lai KB
International Journal of Ophthalmology 2020; 13: 71-78 (IGR: 21-1)


84830 Elevated intraocular pressure induces neuron-specific β-III-tubulin expression in non-neuronal vascular cells
Brockhaus K
Acta Ophthalmologica 2019; 0: (IGR: 21-1)


84988 Accuracy of the ISNT rule and its variants for differentiating glaucomatous from normal eyes in a population-based study
Baudin F
British Journal of Ophthalmology 2020; 0: (IGR: 21-1)


84897 Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images
Park JH
BMC Ophthalmology 2020; 20: 16 (IGR: 21-1)


85025 A neuroglia-based interpretation of glaucomatous neuroretinal rim thinning in the optic nerve head
Han JC
Progress in Retinal and Eye Research 2020; 0: 100840 (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Swanson WH
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


85158 Expression changes in microRNA in the retina of retinal degenerative diseases
Asano D
Nippon yakurigaku zasshi 2020; 155: 81-86 (IGR: 21-1)


85210 The Role of Autophagy in Glaucomatous Optic Neuropathy
Parisi V
Frontiers in cell and developmental biology 2020; 8: 121 (IGR: 21-1)


84822 Evaluation of Papillomacular Nerve Fiber Bundle Thickness in Glaucoma Patients with Visual Acuity Disturbance
Omodaka K
Current Eye Research 2019; 0: 1-7 (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Liu L
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


85159 Pathogenic roles of retinal glia in glaucoma
Koizumi S
Nippon yakurigaku zasshi 2020; 155: 87-92 (IGR: 21-1)


84696 Estimating Visual Field Mean Deviation using Optical Coherence Tomographic Nerve Fiber Layer Measurements in Glaucoma Patients
Greenfield DS
Scientific reports 2019; 9: 18528 (IGR: 21-1)


85051 Vps35 Deficiency Impairs Cdk5/p35 Degradation and Promotes the Hyperphosphorylation of Tau Protein in Retinal Ganglion Cells
Xiao H
Investigative Ophthalmology and Visual Science 2020; 61: 1 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Bae HW
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


84526 Ganglion Cell-Inner Plexiform Layer and Retinal Nerve Fiber Layer Changes in Glaucoma Suspects Enable Prediction of Glaucoma Development
Sung KR
American Journal of Ophthalmology 2020; 210: 26-34 (IGR: 21-1)


84649 Localized Retinal Nerve Fiber Layer Defect Location Among Red-free Fundus Photographs, En Face Structural Images, and Cirrus HD-OCT Maps
Yoo C
Journal of Glaucoma 2019; 28: 1054-1060 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Tan O
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Harris A
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84293 Correlating Structural and Functional Damage in Glaucoma
Hatanaka M
Journal of Glaucoma 2019; 28: 1079-1085 (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Ukegawa K
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


85148 Ganglion Cell Complex Analysis in Glaucoma Patients: What Can It Tell Us?
Fragiotta S
Eye and brain 2020; 12: 33-44 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Luo H
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Moghimi S
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Vasalauskaite A
Brain communications 2019; 1: fcz035 (IGR: 21-1)


84510 Intravitreal S100B Injection Triggers a Time-Dependent Microglia Response in a Pro-Inflammatory Manner in Retina and Optic Nerve
Kuehn S
Molecular Neurobiology 2020; 57: 1186-1202 (IGR: 21-1)


85179 Offline computer-aided diagnosis for Glaucoma detection using fundus images targeted at mobile devices
Cardoso JS
Computer Methods and Programs in Biomedicine 2020; 192: 105341 (IGR: 21-1)


84896 Macular vessel density versus ganglion cell complex thickness for detection of early primary open-angle glaucoma
Xin C
BMC Ophthalmology 2020; 20: 17 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Sasaki M
Scientific reports 2020; 10: 779 (IGR: 21-1)


84536 Retinal nerve fibre layer thickness in a normal black South African population
Ally N
Eye 2019; 0: (IGR: 21-1)


85051 Vps35 Deficiency Impairs Cdk5/p35 Degradation and Promotes the Hyperphosphorylation of Tau Protein in Retinal Ganglion Cells
Ai LQ
Investigative Ophthalmology and Visual Science 2020; 61: 1 (IGR: 21-1)


84978 Comparisons of ganglion cell-inner plexiform layer loss patterns and its diagnostic performance between normal tension glaucoma and primary open angle glaucoma: a detailed, severity-based study
Xiao H
International Journal of Ophthalmology 2020; 13: 71-78 (IGR: 21-1)


85158 Expression changes in microRNA in the retina of retinal degenerative diseases
Morita A
Nippon yakurigaku zasshi 2020; 155: 81-86 (IGR: 21-1)


84988 Accuracy of the ISNT rule and its variants for differentiating glaucomatous from normal eyes in a population-based study
Arnould L
British Journal of Ophthalmology 2020; 0: (IGR: 21-1)


84526 Ganglion Cell-Inner Plexiform Layer and Retinal Nerve Fiber Layer Changes in Glaucoma Suspects Enable Prediction of Glaucoma Development
Song MK
American Journal of Ophthalmology 2020; 210: 26-34 (IGR: 21-1)


84896 Macular vessel density versus ganglion cell complex thickness for detection of early primary open-angle glaucoma
Li M
BMC Ophthalmology 2020; 20: 17 (IGR: 21-1)


85210 The Role of Autophagy in Glaucomatous Optic Neuropathy
Morrone LA
Frontiers in cell and developmental biology 2020; 8: 121 (IGR: 21-1)


84696 Estimating Visual Field Mean Deviation using Optical Coherence Tomographic Nerve Fiber Layer Measurements in Glaucoma Patients
Francis BA
Scientific reports 2019; 9: 18528 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Hardin C
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84536 Retinal nerve fibre layer thickness in a normal black South African population
Alli HD
Eye 2019; 0: (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Motomura K
Scientific reports 2020; 10: 779 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Ing E
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


85222 Assessment of primary open-angle glaucoma peripapillary and macular choroidal area using enhanced depth imaging optical coherence tomography
Nitta E
PLoS ONE 2020; 15: e0231214 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Redmond T
Brain communications 2019; 1: fcz035 (IGR: 21-1)


84766 Peripapillary Vessel Density in Young Patients with Open-Angle Glaucoma: Comparison between High-Tension and Normal-Tension Glaucoma
Kim YY
Scientific reports 2019; 9: 19160 (IGR: 21-1)


84510 Intravitreal S100B Injection Triggers a Time-Dependent Microglia Response in a Pro-Inflammatory Manner in Retina and Optic Nerve
Meißner W
Molecular Neurobiology 2020; 57: 1186-1202 (IGR: 21-1)


84822 Evaluation of Papillomacular Nerve Fiber Bundle Thickness in Glaucoma Patients with Visual Acuity Disturbance
Pak K
Current Eye Research 2019; 0: 1-7 (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Wang J
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Huang L
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Bui BV
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84842 Comparison of glaucoma diagnostic ability of ganglion cell-inner plexiform layer according to the range around the fovea
Kang MS
BMC Ophthalmology 2019; 19: 270 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Owusu-Ansah A
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84830 Elevated intraocular pressure induces neuron-specific β-III-tubulin expression in non-neuronal vascular cells
Anders F
Acta Ophthalmologica 2019; 0: (IGR: 21-1)


85025 A neuroglia-based interpretation of glaucomatous neuroretinal rim thinning in the optic nerve head
Park DY
Progress in Retinal and Eye Research 2020; 0: 100840 (IGR: 21-1)


84900 Temporal Wedge Defects in Glaucoma: Structure / Function Correlation with Threshold Automated Perimetry of the Full Visual Field
Wanzek RJ
Journal of Glaucoma 2020; 0: (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Kim YK
Scientific reports 2019; 9: 19771 (IGR: 21-1)


85179 Offline computer-aided diagnosis for Glaucoma detection using fundus images targeted at mobile devices
Soares F
Computer Methods and Programs in Biomedicine 2020; 192: 105341 (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Klemencic SA
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Proudfoot JA
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


84897 Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images
Jung JH
BMC Ophthalmology 2020; 20: 16 (IGR: 21-1)


84813 Risk factors associated with progressive nerve fiber layer thinning in open-angle glaucoma with mean intraocular pressure below 15 mmHg
Kim CY
Scientific reports 2019; 9: 19811 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Lee SY
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


84649 Localized Retinal Nerve Fiber Layer Defect Location Among Red-free Fundus Photographs, En Face Structural Images, and Cirrus HD-OCT Maps
Kim YY
Journal of Glaucoma 2019; 28: 1054-1060 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Coleman AL
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Nitta E
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


85148 Ganglion Cell Complex Analysis in Glaucoma Patients: What Can It Tell Us?
Scuderi L
Eye and brain 2020; 12: 33-44 (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Zang P
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Yuki K
Scientific reports 2020; 10: 779 (IGR: 21-1)


85025 A neuroglia-based interpretation of glaucomatous neuroretinal rim thinning in the optic nerve head
Kee C
Progress in Retinal and Eye Research 2020; 0: 100840 (IGR: 21-1)


85051 Vps35 Deficiency Impairs Cdk5/p35 Degradation and Promotes the Hyperphosphorylation of Tau Protein in Retinal Ganglion Cells
Chen C
Investigative Ophthalmology and Visual Science 2020; 61: 1 (IGR: 21-1)


84510 Intravitreal S100B Injection Triggers a Time-Dependent Microglia Response in a Pro-Inflammatory Manner in Retina and Optic Nerve
Dick HB
Molecular Neurobiology 2020; 57: 1186-1202 (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Chen B
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Ghahari E
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


84696 Estimating Visual Field Mean Deviation using Optical Coherence Tomographic Nerve Fiber Layer Measurements in Glaucoma Patients
Varma R
Scientific reports 2019; 9: 18528 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Wang YX
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84813 Risk factors associated with progressive nerve fiber layer thinning in open-angle glaucoma with mean intraocular pressure below 15 mmHg
Lee SY
Scientific reports 2019; 9: 19811 (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Jobling AI
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Mensah S
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Wilson MR
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


85148 Ganglion Cell Complex Analysis in Glaucoma Patients: What Can It Tell Us?
Iodice CM
Eye and brain 2020; 12: 33-44 (IGR: 21-1)


84988 Accuracy of the ISNT rule and its variants for differentiating glaucomatous from normal eyes in a population-based study
Seydou A
British Journal of Ophthalmology 2020; 0: (IGR: 21-1)


85210 The Role of Autophagy in Glaucomatous Optic Neuropathy
Corasaniti MT
Frontiers in cell and developmental biology 2020; 8: 121 (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Ueda N
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


84897 Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images
Yoo C
BMC Ophthalmology 2020; 20: 16 (IGR: 21-1)


85222 Assessment of primary open-angle glaucoma peripapillary and macular choroidal area using enhanced depth imaging optical coherence tomography
Sonoda S
PLoS ONE 2020; 15: e0231214 (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Chaglasian M
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Young RD
Brain communications 2019; 1: fcz035 (IGR: 21-1)


85158 Expression changes in microRNA in the retina of retinal degenerative diseases
Mori A
Nippon yakurigaku zasshi 2020; 155: 81-86 (IGR: 21-1)


84896 Macular vessel density versus ganglion cell complex thickness for detection of early primary open-angle glaucoma
Swain DL
BMC Ophthalmology 2020; 20: 17 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Jeoung JW
Scientific reports 2019; 9: 19771 (IGR: 21-1)


84842 Comparison of glaucoma diagnostic ability of ganglion cell-inner plexiform layer according to the range around the fovea
Shin J
BMC Ophthalmology 2019; 19: 270 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Seong GJ
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Morrison JC
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


84900 Temporal Wedge Defects in Glaucoma: Structure / Function Correlation with Threshold Automated Perimetry of the Full Visual Field
Chong LX
Journal of Glaucoma 2020; 0: (IGR: 21-1)


84830 Elevated intraocular pressure induces neuron-specific β-III-tubulin expression in non-neuronal vascular cells
Liu H
Acta Ophthalmologica 2019; 0: (IGR: 21-1)


84978 Comparisons of ganglion cell-inner plexiform layer loss patterns and its diagnostic performance between normal tension glaucoma and primary open angle glaucoma: a detailed, severity-based study
Lin YQ
International Journal of Ophthalmology 2020; 13: 71-78 (IGR: 21-1)


84822 Evaluation of Papillomacular Nerve Fiber Bundle Thickness in Glaucoma Patients with Visual Acuity Disturbance
Kikawa T
Current Eye Research 2019; 0: 1-7 (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Teitelbaum BA
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


84813 Risk factors associated with progressive nerve fiber layer thinning in open-angle glaucoma with mean intraocular pressure below 15 mmHg
Bae HW
Scientific reports 2019; 9: 19811 (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Greferath U
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Edmunds B
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


84897 Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images
Kim YY
BMC Ophthalmology 2020; 20: 16 (IGR: 21-1)


85158 Expression changes in microRNA in the retina of retinal degenerative diseases
Nakahara T
Nippon yakurigaku zasshi 2020; 155: 81-86 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Hassan S
Brain communications 2019; 1: fcz035 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Jeoung JW
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Hayashida Y
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


85148 Ganglion Cell Complex Analysis in Glaucoma Patients: What Can It Tell Us?
Perdicchi A
Eye and brain 2020; 12: 33-44 (IGR: 21-1)


84830 Elevated intraocular pressure induces neuron-specific β-III-tubulin expression in non-neuronal vascular cells
Mercieca K
Acta Ophthalmologica 2019; 0: (IGR: 21-1)


84896 Macular vessel density versus ganglion cell complex thickness for detection of early primary open-angle glaucoma
Cao K
BMC Ophthalmology 2020; 20: 17 (IGR: 21-1)


85051 Vps35 Deficiency Impairs Cdk5/p35 Degradation and Promotes the Hyperphosphorylation of Tau Protein in Retinal Ganglion Cells
Lin S
Investigative Ophthalmology and Visual Science 2020; 61: 1 (IGR: 21-1)


85106 Hierarchical Cluster Analysis of Peripapillary Retinal Nerve Fiber Layer Damage and Macular Ganglion Cell Loss in Open Angle Glaucoma
Kim CY
Korean Journal of Ophthalmology 2020; 34: 56-66 (IGR: 21-1)


84978 Comparisons of ganglion cell-inner plexiform layer loss patterns and its diagnostic performance between normal tension glaucoma and primary open angle glaucoma: a detailed, severity-based study
Guo XX
International Journal of Ophthalmology 2020; 13: 71-78 (IGR: 21-1)


84510 Intravitreal S100B Injection Triggers a Time-Dependent Microglia Response in a Pro-Inflammatory Manner in Retina and Optic Nerve
Joachim SC
Molecular Neurobiology 2020; 57: 1186-1202 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Edmunds B
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


84822 Evaluation of Papillomacular Nerve Fiber Bundle Thickness in Glaucoma Patients with Visual Acuity Disturbance
Kobayashi W
Current Eye Research 2019; 0: 1-7 (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Yang J
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


84900 Temporal Wedge Defects in Glaucoma: Structure / Function Correlation with Threshold Automated Perimetry of the Full Visual Field
Turpin A
Journal of Glaucoma 2020; 0: (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Oduro-Boateng J
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Founti P
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84988 Accuracy of the ISNT rule and its variants for differentiating glaucomatous from normal eyes in a population-based study
Binquet C
British Journal of Ophthalmology 2020; 0: (IGR: 21-1)


85210 The Role of Autophagy in Glaucomatous Optic Neuropathy
Bagetta G
Frontiers in cell and developmental biology 2020; 8: 121 (IGR: 21-1)


84696 Estimating Visual Field Mean Deviation using Optical Coherence Tomographic Nerve Fiber Layer Measurements in Glaucoma Patients
Schuman JS
Scientific reports 2019; 9: 18528 (IGR: 21-1)


85222 Assessment of primary open-angle glaucoma peripapillary and macular choroidal area using enhanced depth imaging optical coherence tomography
Sakamoto T
PLoS ONE 2020; 15: e0231214 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Kim HC
Scientific reports 2019; 9: 19771 (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Penteado RC
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Kurihara T
Scientific reports 2020; 10: 779 (IGR: 21-1)


85051 Vps35 Deficiency Impairs Cdk5/p35 Degradation and Promotes the Hyperphosphorylation of Tau Protein in Retinal Ganglion Cells
Zhou Y
Investigative Ophthalmology and Visual Science 2020; 61: 1 (IGR: 21-1)


84830 Elevated intraocular pressure induces neuron-specific β-III-tubulin expression in non-neuronal vascular cells
Gericke A
Acta Ophthalmologica 2019; 0: (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Yu F
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Brandli A
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84822 Evaluation of Papillomacular Nerve Fiber Bundle Thickness in Glaucoma Patients with Visual Acuity Disturbance
Akiba M
Current Eye Research 2019; 0: 1-7 (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Lombardi L
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


84896 Macular vessel density versus ganglion cell complex thickness for detection of early primary open-angle glaucoma
Wang H
BMC Ophthalmology 2020; 20: 17 (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Clark CA
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


84978 Comparisons of ganglion cell-inner plexiform layer loss patterns and its diagnostic performance between normal tension glaucoma and primary open angle glaucoma: a detailed, severity-based study
Liu X
International Journal of Ophthalmology 2020; 13: 71-78 (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Bowd C
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


85222 Assessment of primary open-angle glaucoma peripapillary and macular choroidal area using enhanced depth imaging optical coherence tomography
Kiuchi Y
PLoS ONE 2020; 15: e0231214 (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Hirama H
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


84814 Automated Quantification of Macular Ellipsoid Zone Intensity in Glaucoma Patients: the Method and its Comparison with Manual Quantification
Park KH
Scientific reports 2019; 9: 19771 (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Lu J
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Tomita Y
Scientific reports 2020; 10: 779 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Davis E
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Albert C
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Kojo RA
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84988 Accuracy of the ISNT rule and its variants for differentiating glaucomatous from normal eyes in a population-based study
Bron AM
British Journal of Ophthalmology 2020; 0: (IGR: 21-1)


85210 The Role of Autophagy in Glaucomatous Optic Neuropathy
Tonin P
Frontiers in cell and developmental biology 2020; 8: 121 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Fautsch MP
Brain communications 2019; 1: fcz035 (IGR: 21-1)


84696 Estimating Visual Field Mean Deviation using Optical Coherence Tomographic Nerve Fiber Layer Measurements in Glaucoma Patients
Huang D
Scientific reports 2019; 9: 18528 (IGR: 21-1)


84822 Evaluation of Papillomacular Nerve Fiber Bundle Thickness in Glaucoma Patients with Visual Acuity Disturbance
Nakazawa T
Current Eye Research 2019; 0: 1-7 (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Speilburg AM
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


85210 The Role of Autophagy in Glaucomatous Optic Neuropathy
Russo R
Frontiers in cell and developmental biology 2020; 8: 121 (IGR: 21-1)


84988 Accuracy of the ISNT rule and its variants for differentiating glaucomatous from normal eyes in a population-based study
Creuzot-Garcher CP
British Journal of Ophthalmology 2020; 0: (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Davis E
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Gupta S
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Sengpiel F
Brain communications 2019; 1: fcz035 (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Yang D
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


84896 Macular vessel density versus ganglion cell complex thickness for detection of early primary open-angle glaucoma
Wang N
BMC Ophthalmology 2020; 20: 17 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Kyei S
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


85051 Vps35 Deficiency Impairs Cdk5/p35 Degradation and Promotes the Hyperphosphorylation of Tau Protein in Retinal Ganglion Cells
Ye J
Investigative Ophthalmology and Visual Science 2020; 61: 1 (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Qiao T
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Ozawa Y
Scientific reports 2020; 10: 779 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Siesky B
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Taoka R
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Vianna JR
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Dixon MA
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84830 Elevated intraocular pressure induces neuron-specific β-III-tubulin expression in non-neuronal vascular cells
Melkonyan H
Acta Ophthalmologica 2019; 0: (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Grogg JA
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Williams PA
Brain communications 2019; 1: fcz035 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Anastasopoulos E
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


85134 Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma
Weinreb RN
Ophthalmology 2020; 127: 1043-1052 (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Sakura Y
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Boadi-Kusi SB
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Sharpe GP
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Findlay Q
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84830 Elevated intraocular pressure induces neuron-specific β-III-tubulin expression in non-neuronal vascular cells
Thanos S
Acta Ophthalmologica 2019; 0: (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Morrison JC
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Yamagishi K
Scientific reports 2020; 10: 779 (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Fan Z
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Lombardi LH
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


85051 Vps35 Deficiency Impairs Cdk5/p35 Degradation and Promotes the Hyperphosphorylation of Tau Protein in Retinal Ganglion Cells
Liu W
Investigative Ophthalmology and Visual Science 2020; 61: 1 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Reynaud J
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84698 Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model
Zhang M
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 577-585 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Jia Y
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


84852 Midget retinal ganglion cell dendritic and mitochondrial degeneration is an early feature of human glaucoma
Morgan JE
Brain communications 2019; 1: fcz035 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Kawasaki R
Scientific reports 2020; 10: 779 (IGR: 21-1)


85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Peabody TD
Optometry and Vision Science 2020; 97: 54-61 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Pappas T
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Jia Y
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Amoah-Smith O
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Yamasaki M
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Fletcher EL
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Morny EKA
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84613 Sectorwise Visual Field Simulation Using Optical Coherence Tomographic Angiography Nerve Fiber Layer Plexus Measurements in Glaucoma
Huang D
American Journal of Ophthalmology 2020; 212: 57-68 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Hanyuda A
Scientific reports 2020; 10: 779 (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Tsunemori H
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


84756 Potential mechanisms of retinal ganglion cell type-specific vulnerability in glaucoma
Vessey KA
Clinical and Experimental Optometry 2019; 0: (IGR: 21-1)


84860 Measuring Glaucomatous Focal Perfusion Loss in the Peripapillary Retina Using OCT Angiography
Huang D
Ophthalmology 2020; 127: 484-491 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Demirel S
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Koskosas A
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Sugimoto M
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Darko-Takyi C
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Kilintzis V
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Mansberger SL
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Sawada N
Scientific reports 2020; 10: 779 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Fortune B
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Abraham CH
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Tsubota K
Scientific reports 2020; 10: 779 (IGR: 21-1)


84632 Factors associated with non-active retinal capillary density as measured with Confocal Scanning Laser Doppler Flowmetry in an elderly population: the Thessaloniki Eye Study (TES)
Topouzis F
British Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84836 Retinal Nerve Fiber Layer Thickness Progression after Robotic-Assisted Laparoscopic Radical Prostatectomy in Glaucoma Patients
Kiuchi Y
Journal of Ophthalmology 2019; 2019: 6576140 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Appiah Nyamekye B
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Nicolela M
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Tsugane S
Scientific reports 2020; 10: 779 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Gardiner SK
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Iso H
Scientific reports 2020; 10: 779 (IGR: 21-1)


85152 Normative Values of Retinal Nerve Fibre Layer Thickness and Optic Nerve Head Parameters and Their Association with Visual Function in an African Population
Ilechie AA
Journal of Ophthalmology 2020; 2020: 7150673 (IGR: 21-1)


84861 OCT Structural Abnormality Detection in Glaucoma using Topographically Correspondent Rim and Retinal Nerve Fiber Layer Criteria
Chauhan BC; Burgoyne CF
American Journal of Ophthalmology 2019; 0: (IGR: 21-1)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Liu Y
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82817 New Circumpapillary Retinal Nerve Fiber Layer Thickness and Bruch's Membrane Opening-Minimum Rim Width Assessment in Nonglaucomatous Eyes with Large Discs
Bayraktar S
Journal of Ophthalmology 2019; 2019: 3431217 (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Bochicchio S
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


82305 The correlation between the thickness of the inner macular layers and the mean deviation of the visual field in children with primary congenital glaucoma
Nieves-Moreno M
Archivos de la Sociedad Espa˝ola de Oftalmologia 2019; 94: 536-539 (IGR: 20-4)


82610 Influence of Epiretinal Membranes on the Retinal Nerve Fiber Layer Thickness Measured by Spectral Domain Optical Coherence Tomography in Glaucoma
Kim JM
Korean Journal of Ophthalmology 2019; 33: 422-429 (IGR: 20-4)


82748 Vessel density and retinal nerve fibre layer thickness following acute primary angle closure
Moghimi S
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Amil P
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82364 Analysis of the Optic Disc and Peripapillary Structures in Monozygotic Twins
Park DY
Journal of Glaucoma 2019; 28: 969-973 (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Li D
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Yohannan J
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82394 OCT Angiography: Measurement of Retinal Macular Microvasculature with Spectralis II OCT Angiography - Reliability and Reproducibility
Hosari S
Ophthalmologica 2020; 243: 75-84 (IGR: 20-4)


82674 Structural evaluation of preperimetric and perimetric glaucoma
Deshpande G
Indian Journal of Ophthalmology 2019; 67: 1843-1849 (IGR: 20-4)


82220 Effect of surgical intraocular pressure lowering on retinal structures - nerve fibre layer, foveal avascular zone, peripapillary and macular vessel density: 1 year results
Ch'ng TW
Eye 2020; 34: 562-571 (IGR: 20-4)


82523 Structure-function Relationship in Advanced Glaucoma After Reaching the RNFL Floor
Sung MS
Journal of Glaucoma 2019; 28: 1006-1011 (IGR: 20-4)


82134 Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma
Lee EJ
Investigative Ophthalmology and Visual Science 2019; 60: 3343-3351 (IGR: 20-4)


82487 Relationship between preoperative high intraocular pressure and retinal nerve fibre layer thinning after glaucoma surgery
Kim WJ
Scientific reports 2019; 9: 13901 (IGR: 20-4)


82656 Localized Retinal Nerve Fiber Layer Defect Location among Red-free Fundus Photograph, En Face Structural Image, and Cirrus HD-OCT Maps
Park JH
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82200 Rate of three-dimensional neuroretinal rim thinning in glaucomatous eyes with optic disc haemorrhage
Kim YW
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82764 Does Retinal Ganglion Cell Loss Precede Visual Field Loss in Glaucoma?
Hood DC
Journal of Glaucoma 2019; 28: 945-951 (IGR: 20-4)


82394 OCT Angiography: Measurement of Retinal Macular Microvasculature with Spectralis II OCT Angiography - Reliability and Reproducibility
Hosari S
Ophthalmologica 2020; 243: 75-84 (IGR: 20-4)


82707 Potential Impact of DARC Technology in Neuroprotective Therapies
Pahlitzsch M
Klinische Monatsblńtter fŘr Augenheilkunde 2020; 237: 140-142 (IGR: 20-4)


82001 Axon injury signaling and compartmentalized injury response in glaucoma
Syc-Mazurek SB
Progress in Retinal and Eye Research 2019; 73: 100769 (IGR: 20-4)


82624 Thinning rates of retinal nerve layer and ganglion cell-inner plexiform layer in various stages of normal tension glaucoma
Inuzuka H
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82185 Location of Retinal Nerve Fiber Layer Defects in Open-angle Glaucoma and Associated Factors
Kim HU
Korean Journal of Ophthalmology 2019; 33: 379-385 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Liao W
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
Casado A
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82666 Relationship of the Macular Ganglion Cell and Inner Plexiform Layers in Healthy and Glaucoma Eyes
Moghimi S
Translational vision science & technology 2019; 8: 27 (IGR: 20-4)


82299 Effect of Foveal Location on Retinal Nerve Fiber Layer Thickness Profile in Superior Oblique Palsy Eyes
Akbari M
Journal of Glaucoma 2019; 28: 916-921 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Chiquet C
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Wu Z
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82039 Temporal change of retinal nerve fiber layer reflectance speckle in normal and hypertensive retinas
Huang XR
Experimental Eye Research 2019; 186: 107738 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Tao Y
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Qin X
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82557 Assessment of Ganglion Cell Complex and Peripapillary Retinal Nerve Fiber Layer Changes following Cataract Surgery in Patients with Pseudoexfoliation Glaucoma
Abdelghany AA
Journal of Ophthalmology 2019; 2019: 8162825 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Mavrommatis MA
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82340 Characteristics of Patients Showing Discrepancy Between Bruch's Membrane Opening-Minimum Rim Width and Peripapillary Retinal Nerve Fiber Layer Thickness
Cho HK
Journal of clinical medicine 2019; 8: (IGR: 20-4)


82618 Within-subject variability in human retinal nerve fiber bundle width
Swanson WH
PLoS ONE 2019; 14: e0223350 (IGR: 20-4)


82299 Effect of Foveal Location on Retinal Nerve Fiber Layer Thickness Profile in Superior Oblique Palsy Eyes
Nikdel M
Journal of Glaucoma 2019; 28: 916-921 (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Li N
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
De Cuir N
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82340 Characteristics of Patients Showing Discrepancy Between Bruch's Membrane Opening-Minimum Rim Width and Peripapillary Retinal Nerve Fiber Layer Thickness
Kee C
Journal of clinical medicine 2019; 8: (IGR: 20-4)


82748 Vessel density and retinal nerve fibre layer thickness following acute primary angle closure
Safizadeh M
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Reyes-Manzano CF
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zou B
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82039 Temporal change of retinal nerve fiber layer reflectance speckle in normal and hypertensive retinas
Knighton RW
Experimental Eye Research 2019; 186: 107738 (IGR: 20-4)


82618 Within-subject variability in human retinal nerve fiber bundle width
King BJ
PLoS ONE 2019; 14: e0223350 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Tham YC
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82674 Structural evaluation of preperimetric and perimetric glaucoma
Gupta R
Indian Journal of Ophthalmology 2019; 67: 1843-1849 (IGR: 20-4)


82220 Effect of surgical intraocular pressure lowering on retinal structures - nerve fibre layer, foveal avascular zone, peripapillary and macular vessel density: 1 year results
Gillmann K
Eye 2020; 34: 562-571 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Gavard O
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Vianna JR
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82305 The correlation between the thickness of the inner macular layers and the mean deviation of the visual field in children with primary congenital glaucoma
García-Caride S
Archivos de la Sociedad Espa˝ola de Oftalmologia 2019; 94: 536-539 (IGR: 20-4)


82610 Influence of Epiretinal Membranes on the Retinal Nerve Fiber Layer Thickness Measured by Spectral Domain Optical Coherence Tomography in Glaucoma
Kim KN
Korean Journal of Ophthalmology 2019; 33: 422-429 (IGR: 20-4)


82557 Assessment of Ganglion Cell Complex and Peripapillary Retinal Nerve Fiber Layer Changes following Cataract Surgery in Patients with Pseudoexfoliation Glaucoma
Sallam MA
Journal of Ophthalmology 2019; 2019: 8162825 (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Rauscher FG
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Jassim F
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82487 Relationship between preoperative high intraocular pressure and retinal nerve fibre layer thinning after glaucoma surgery
Kim KN
Scientific reports 2019; 9: 13901 (IGR: 20-4)


82656 Localized Retinal Nerve Fiber Layer Defect Location among Red-free Fundus Photograph, En Face Structural Image, and Cirrus HD-OCT Maps
Yoo C
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82666 Relationship of the Macular Ganglion Cell and Inner Plexiform Layers in Healthy and Glaucoma Eyes
Fatehi N
Translational vision science & technology 2019; 8: 27 (IGR: 20-4)


82523 Structure-function Relationship in Advanced Glaucoma After Reaching the RNFL Floor
Heo H
Journal of Glaucoma 2019; 28: 1006-1011 (IGR: 20-4)


82001 Axon injury signaling and compartmentalized injury response in glaucoma
Libby RT
Progress in Retinal and Eye Research 2019; 73: 100769 (IGR: 20-4)


82134 Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma
Kim TW
Investigative Ophthalmology and Visual Science 2019; 60: 3343-3351 (IGR: 20-4)


82624 Thinning rates of retinal nerve layer and ganglion cell-inner plexiform layer in various stages of normal tension glaucoma
Sawada A
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82185 Location of Retinal Nerve Fiber Layer Defects in Open-angle Glaucoma and Associated Factors
Na KI
Korean Journal of Ophthalmology 2019; 33: 379-385 (IGR: 20-4)


82364 Analysis of the Optic Disc and Peripapillary Structures in Monozygotic Twins
Han JC
Journal of Glaucoma 2019; 28: 969-973 (IGR: 20-4)


82200 Rate of three-dimensional neuroretinal rim thinning in glaucomatous eyes with optic disc haemorrhage
Lee WJ
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82817 New Circumpapillary Retinal Nerve Fiber Layer Thickness and Bruch's Membrane Opening-Minimum Rim Width Assessment in Nonglaucomatous Eyes with Large Discs
Sultanova G
Journal of Ophthalmology 2019; 2019: 3431217 (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Milani P
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Cheng M
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82394 OCT Angiography: Measurement of Retinal Macular Microvasculature with Spectralis II OCT Angiography - Reliability and Reproducibility
Hohberger B
Ophthalmologica 2020; 243: 75-84 (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
Cerveró A
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82666 Relationship of the Macular Ganglion Cell and Inner Plexiform Layers in Healthy and Glaucoma Eyes
Nguyen AH
Translational vision science & technology 2019; 8: 27 (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Da J
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82674 Structural evaluation of preperimetric and perimetric glaucoma
Bawankule P
Indian Journal of Ophthalmology 2019; 67: 1843-1849 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Arnould L
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Reynaud J
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82487 Relationship between preoperative high intraocular pressure and retinal nerve fibre layer thinning after glaucoma surgery
Sung JY
Scientific reports 2019; 9: 13901 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zhao R
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82557 Assessment of Ganglion Cell Complex and Peripapillary Retinal Nerve Fiber Layer Changes following Cataract Surgery in Patients with Pseudoexfoliation Glaucoma
Ellabban AA
Journal of Ophthalmology 2019; 2019: 8162825 (IGR: 20-4)


82200 Rate of three-dimensional neuroretinal rim thinning in glaucomatous eyes with optic disc haemorrhage
Seol BR
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82817 New Circumpapillary Retinal Nerve Fiber Layer Thickness and Bruch's Membrane Opening-Minimum Rim Width Assessment in Nonglaucomatous Eyes with Large Discs
Cebeci Z
Journal of Ophthalmology 2019; 2019: 3431217 (IGR: 20-4)


82610 Influence of Epiretinal Membranes on the Retinal Nerve Fiber Layer Thickness Measured by Spectral Domain Optical Coherence Tomography in Glaucoma
Kim WJ
Korean Journal of Ophthalmology 2019; 33: 422-429 (IGR: 20-4)


82624 Thinning rates of retinal nerve layer and ganglion cell-inner plexiform layer in various stages of normal tension glaucoma
Inuzuka M
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Urbini LE
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Braaf B
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82364 Analysis of the Optic Disc and Peripapillary Structures in Monozygotic Twins
Lee EJ
Journal of Glaucoma 2019; 28: 969-973 (IGR: 20-4)


82523 Structure-function Relationship in Advanced Glaucoma After Reaching the RNFL Floor
Park SW
Journal of Glaucoma 2019; 28: 1006-1011 (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Zhang M
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Chee ML
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82394 OCT Angiography: Measurement of Retinal Macular Microvasculature with Spectralis II OCT Angiography - Reliability and Reproducibility
Theelke L
Ophthalmologica 2020; 243: 75-84 (IGR: 20-4)


82674 Structural evaluation of preperimetric and perimetric glaucoma
Bawankule P
Indian Journal of Ophthalmology 2019; 67: 1843-1849 (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
López-de-Eguileta A
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82618 Within-subject variability in human retinal nerve fiber bundle width
Burns SA
PLoS ONE 2019; 14: e0223350 (IGR: 20-4)


82748 Vessel density and retinal nerve fibre layer thickness following acute primary angle closure
Xu BY
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82220 Effect of surgical intraocular pressure lowering on retinal structures - nerve fibre layer, foveal avascular zone, peripapillary and macular vessel density: 1 year results
Hoskens K
Eye 2020; 34: 562-571 (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Choi EY
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Reis ASC
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82039 Temporal change of retinal nerve fiber layer reflectance speckle in normal and hypertensive retinas
Spector YZ
Experimental Eye Research 2019; 186: 107738 (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Guzmán-Vargas L
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Chee ML
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82299 Effect of Foveal Location on Retinal Nerve Fiber Layer Thickness Profile in Superior Oblique Palsy Eyes
Moghimi S
Journal of Glaucoma 2019; 28: 916-921 (IGR: 20-4)


82305 The correlation between the thickness of the inner macular layers and the mean deviation of the visual field in children with primary congenital glaucoma
Morales-Fernandez L
Archivos de la Sociedad Espa˝ola de Oftalmologia 2019; 94: 536-539 (IGR: 20-4)


82134 Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma
Kim JA
Investigative Ophthalmology and Visual Science 2019; 60: 3343-3351 (IGR: 20-4)


82656 Localized Retinal Nerve Fiber Layer Defect Location among Red-free Fundus Photograph, En Face Structural Image, and Cirrus HD-OCT Maps
Kim YY
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82220 Effect of surgical intraocular pressure lowering on retinal structures - nerve fibre layer, foveal avascular zone, peripapillary and macular vessel density: 1 year results
Rao HL
Eye 2020; 34: 562-571 (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Khoueir Z
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82039 Temporal change of retinal nerve fiber layer reflectance speckle in normal and hypertensive retinas
Kong W
Experimental Eye Research 2019; 186: 107738 (IGR: 20-4)


82134 Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma
Kim GN
Investigative Ophthalmology and Visual Science 2019; 60: 3343-3351 (IGR: 20-4)


82624 Thinning rates of retinal nerve layer and ganglion cell-inner plexiform layer in various stages of normal tension glaucoma
Yamamoto T
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82666 Relationship of the Macular Ganglion Cell and Inner Plexiform Layers in Healthy and Glaucoma Eyes
Romero P
Translational vision science & technology 2019; 8: 27 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Majithia S
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Chapagain S
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82299 Effect of Foveal Location on Retinal Nerve Fiber Layer Thickness Profile in Superior Oblique Palsy Eyes
Subramanian PS
Journal of Glaucoma 2019; 28: 916-921 (IGR: 20-4)


82817 New Circumpapillary Retinal Nerve Fiber Layer Thickness and Bruch's Membrane Opening-Minimum Rim Width Assessment in Nonglaucomatous Eyes with Large Discs
Altinkurt E
Journal of Ophthalmology 2019; 2019: 3431217 (IGR: 20-4)


82305 The correlation between the thickness of the inner macular layers and the mean deviation of the visual field in children with primary congenital glaucoma
Martínez-de-la-Casa JM
Archivos de la Sociedad Espa˝ola de Oftalmologia 2019; 94: 536-539 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Zemborain ZZ
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Chen Y
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82364 Analysis of the Optic Disc and Peripapillary Structures in Monozygotic Twins
Kee C
Journal of Glaucoma 2019; 28: 969-973 (IGR: 20-4)


82200 Rate of three-dimensional neuroretinal rim thinning in glaucomatous eyes with optic disc haemorrhage
Kim YK
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Bulone E
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
De Moraes CG
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
Fernández R
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82610 Influence of Epiretinal Membranes on the Retinal Nerve Fiber Layer Thickness Measured by Spectral Domain Optical Coherence Tomography in Glaucoma
Kim CS
Korean Journal of Ophthalmology 2019; 33: 422-429 (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Wang M
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82394 OCT Angiography: Measurement of Retinal Macular Microvasculature with Spectralis II OCT Angiography - Reliability and Reproducibility
Sari H
Ophthalmologica 2020; 243: 75-84 (IGR: 20-4)


82674 Structural evaluation of preperimetric and perimetric glaucoma
Raje D
Indian Journal of Ophthalmology 2019; 67: 1843-1849 (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Lin S
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Mautuit T
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82487 Relationship between preoperative high intraocular pressure and retinal nerve fibre layer thinning after glaucoma surgery
Kim JY
Scientific reports 2019; 9: 13901 (IGR: 20-4)


82748 Vessel density and retinal nerve fibre layer thickness following acute primary angle closure
Fard MA
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Sendiña-Nadal I
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82134 Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma
Kim JM
Investigative Ophthalmology and Visual Science 2019; 60: 3343-3351 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Thakur S
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Poon LY
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Macgillivray TJ
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82487 Relationship between preoperative high intraocular pressure and retinal nerve fibre layer thinning after glaucoma surgery
Kim CS
Scientific reports 2019; 9: 13901 (IGR: 20-4)


82200 Rate of three-dimensional neuroretinal rim thinning in glaucomatous eyes with optic disc haemorrhage
Jeoung JW
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
Fonseca S
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82220 Effect of surgical intraocular pressure lowering on retinal structures - nerve fibre layer, foveal avascular zone, peripapillary and macular vessel density: 1 year results
Mermoud A
Eye 2020; 34: 562-571 (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Baniasadi N
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Lee SH
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82305 The correlation between the thickness of the inner macular layers and the mean deviation of the visual field in children with primary congenital glaucoma
Sáenz-Francés F
Archivos de la Sociedad Espa˝ola de Oftalmologia 2019; 94: 536-539 (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
He Z
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


82039 Temporal change of retinal nerve fiber layer reflectance speckle in normal and hypertensive retinas
Qiao J
Experimental Eye Research 2019; 186: 107738 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Xin D
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82748 Vessel density and retinal nerve fibre layer thickness following acute primary angle closure
Khatibi N
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82088 Network-based features for retinal fundus vessel structure analysis
Masoller C
PLoS ONE 2019; 14: e0220132 (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Zhu J
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82394 OCT Angiography: Measurement of Retinal Macular Microvasculature with Spectralis II OCT Angiography - Reliability and Reproducibility
Lucio M
Ophthalmologica 2020; 243: 75-84 (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Sotimehin A
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82674 Structural evaluation of preperimetric and perimetric glaucoma
Chakarborty M
Indian Journal of Ophthalmology 2019; 67: 1843-1849 (IGR: 20-4)


82299 Effect of Foveal Location on Retinal Nerve Fiber Layer Thickness Profile in Superior Oblique Palsy Eyes
Fard MA
Journal of Glaucoma 2019; 28: 916-921 (IGR: 20-4)


82817 New Circumpapillary Retinal Nerve Fiber Layer Thickness and Bruch's Membrane Opening-Minimum Rim Width Assessment in Nonglaucomatous Eyes with Large Discs
Izgi B
Journal of Ophthalmology 2019; 2019: 3431217 (IGR: 20-4)


82666 Relationship of the Macular Ganglion Cell and Inner Plexiform Layers in Healthy and Glaucoma Eyes
Caprioli J
Translational vision science & technology 2019; 8: 27 (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Carmassi L
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Soh ZD
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82666 Relationship of the Macular Ganglion Cell and Inner Plexiform Layers in Healthy and Glaucoma Eyes
Nouri-Mahdavi K
Translational vision science & technology 2019; 8: 27 (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Fratantonio E
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Thenappan A
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Xiao D
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
González JC
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82394 OCT Angiography: Measurement of Retinal Macular Microvasculature with Spectralis II OCT Angiography - Reliability and Reproducibility
Mardin CY
Ophthalmologica 2020; 243: 75-84 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Bron AM
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Rajshekhar R
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82134 Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma
Girard MJA
Investigative Ophthalmology and Visual Science 2019; 60: 3343-3351 (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Wirkner K
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82220 Effect of surgical intraocular pressure lowering on retinal structures - nerve fibre layer, foveal avascular zone, peripapillary and macular vessel density: 1 year results
Mansouri K
Eye 2020; 34: 562-571 (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Bonham LW
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Rajshekhar R
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82305 The correlation between the thickness of the inner macular layers and the mean deviation of the visual field in children with primary congenital glaucoma
Sánchez-Jean R
Archivos de la Sociedad Espa˝ola de Oftalmologia 2019; 94: 536-539 (IGR: 20-4)


82748 Vessel density and retinal nerve fibre layer thickness following acute primary angle closure
Rao HL
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82691 Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
Zhou M
IEEE journal of biomedical and health informatics 2019; 0: (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Ben-David GS
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82200 Rate of three-dimensional neuroretinal rim thinning in glaucomatous eyes with optic disc haemorrhage
Park KH
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Kirsten T
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Cheung CY
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Weng DSD
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Papadogeorgou G
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Liebmann JM
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82748 Vessel density and retinal nerve fibre layer thickness following acute primary angle closure
Weinreb RN
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
Pacheco G
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Mihailovic A
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82305 The correlation between the thickness of the inner macular layers and the mean deviation of the visual field in children with primary congenital glaucoma
Santos-Bueso E
Archivos de la Sociedad Espa˝ola de Oftalmologia 2019; 94: 536-539 (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Castegna G
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Cui W
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Weng DSD
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Semecas R
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82134 Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma
Mari JM
Investigative Ophthalmology and Visual Science 2019; 60: 3343-3351 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Weng DSD
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82305 The correlation between the thickness of the inner macular layers and the mean deviation of the visual field in children with primary congenital glaucoma
García-Feijoo J
Archivos de la Sociedad Espa˝ola de Oftalmologia 2019; 94: 536-539 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Tsamis E
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Trucco E
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Tsamis E
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
Gándara E
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82134 Elucidation of the Strongest Factors Influencing Rapid Retinal Nerve Fiber Layer Thinning in Glaucoma
Kim H
Investigative Ophthalmology and Visual Science 2019; 60: 3343-3351 (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Scotti L
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Tsikata E
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Boland M
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Thiery J
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Ritch R
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Tsamis E
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Zhang T
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Sabanayagam C
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Joiner DB
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Engel C
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Lin Y
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Zambon A
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Simavli H
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Fortune B
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82697 Evidence-Based Criteria for Determining Peripapillary OCT Reliability
Ramulu P
Ophthalmology 2020; 127: 167-176 (IGR: 20-4)


82110 Retinal vessel phenotype in patients with primary open-angle glaucoma
Florent A
Acta Ophthalmologica 2020; 98: e88-e93 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Joiner DB
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Wong TY
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82393 Topographic correlation and asymmetry analysis of ganglion cell layer thinning and the retinal nerve fiber layer with localized visual field defects
Gordo-Vega MÁ
PLoS ONE 2019; 14: e0222347 (IGR: 20-4)


82686 Tetrahedral framework nucleic acids prevent retina ischemia-reperfusion injury from oxidative stress via activating the Akt/Nrf2 pathway
Cai X
Nanoscale 2019; 11: 20667-20675 (IGR: 20-4)


82063 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Hood DC
Journal of Glaucoma 2019; 0: (IGR: 20-4)


82494 Profile of retinal nerve fibre layer symmetry in a multiethnic Asian population: the Singapore Epidemiology of Eye Diseases study
Cheng CY
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Loeffler M
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82531 Diurnal Stability Of Peripapillary Vessel Density And Nerve Fiber Layer Thickness On Optical Coherence Tomography Angiography In Healthy, Ocular Hypertension And Glaucoma Eyes
Bergamini F
Clinical Ophthalmology 2019; 13: 1823-1832 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Ritch R
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Que C
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82797 Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness
Elze T
Ophthalmology 2020; 127: 357-368 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
De Moraes CGV
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Lee R
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


82723 Qualitative evaluation of neuroretinal rim and retinal nerve fibre layer on optical coherence tomography to detect glaucomatous damage
Hood DC
British Journal of Ophthalmology 2019; 0: (IGR: 20-4)


81842 Diagnostic Capability of 3D Peripapillary Retinal Volume for Glaucoma Using Optical Coherence Tomography Customized Software
Shieh E; Vakoc BJ; Bouma BE; de Boer JF; Chen TC
Journal of Glaucoma 2019; 28: 708-717 (IGR: 20-4)


81359 Investigation of the Presence of Glaucoma in Patients with Obstructive Sleep Apnea Syndrome Using and Not Using Continuous Positive Airway Pressure Treatment
Abdullayev A
Turkish journal of ophthalmology 2019; 49: 134-141 (IGR: 20-3)


80919 Effects of chronic elevated intraocular pressure on parameters of optical coherence tomography in rhesus monkeys
Yan ZC
International Journal of Ophthalmology 2019; 12: 542-548 (IGR: 20-3)


81431 Detection and characterisation of optic nerve and retinal changes in primary congenital glaucoma using hand-held optical coherence tomography
Pilat AV
BMJ open ophthalmology 2019; 4: e000194 (IGR: 20-3)


80645 Association of Macular and Circumpapillary Microvasculature with Visual Field Sensitivity in Advanced Glaucoma
Ghahari E
American Journal of Ophthalmology 2019; 204: 51-61 (IGR: 20-3)


81177 Joint retina segmentation and classification for early glaucoma diagnosis
Wang J
Biomedical optics express 2019; 10: 2639-2656 (IGR: 20-3)


80461 Association Between Lamina Cribrosa Defects and Progressive Retinal Nerve Fiber Layer Loss in Glaucoma
Moghimi S
JAMA ophthalmology 2019; 137: 425-433 (IGR: 20-3)


81190 Acute angle closure glaucoma from spontaneous massive subretinal hemorrhage
Sosuan GMN
GMS ophthalmology cases 2019; 9: Doc15 (IGR: 20-3)


80742 Discriminating performance of macular ganglion cell-inner plexiform layer thicknesses at different stages of glaucoma
Ustaoglu M
International Journal of Ophthalmology 2019; 12: 464-471 (IGR: 20-3)


80988 Intereye and intraeye asymmetry analysis of retinal microvascular and neural structure parameters for diagnosis of primary open-angle glaucoma
Xu H
Eye 2019; 33: 1596-1605 (IGR: 20-3)


81241 Determinants of Macular Layers and Optic Disc Characteristics on SD-OCT: The Rhineland Study
Mauschitz MM
Translational vision science & technology 2019; 8: 34 (IGR: 20-3)


81422 Two-year analysis of changes in the optic nerve and retina following anti-VEGF treatments in diabetic macular edema patients
Filek R
Clinical Ophthalmology 2019; 13: 1087-1096 (IGR: 20-3)


81216 Projection-Resolved Optical Coherence Tomography Angiography of the Peripapillary Retina in Glaucoma
Liu L
American Journal of Ophthalmology 2019; 207: 99-109 (IGR: 20-3)


81460 Diagnostic Ability of Macular Vessel Density in the Ganglion Cell-Inner Plexiform Layer on Optical Coherence Tomographic Angiography for Glaucoma
Shin J
Translational vision science & technology 2019; 8: 12 (IGR: 20-3)


80803 Macular ganglion cell-inner plexiform vs retinal nerve fiber layer measurement to detect early glaucoma with superior or inferior hemifield defects
Chen MJ
Journal of the Chinese Medical Association 2019; 82: 335-339 (IGR: 20-3)


81109 Compensation of retinal nerve fibre layer thickness as assessed using optical coherence tomography based on anatomical confounders
Chua J
British Journal of Ophthalmology 2020; 104: 282-290 (IGR: 20-3)


81319 An in vitro pressure model towards studying the response of primary retinal ganglion cells to elevated hydrostatic pressures
Wu J
Scientific reports 2019; 9: 9057 (IGR: 20-3)


81384 A feature agnostic approach for glaucoma detection in OCT volumes
Maetschke S
PLoS ONE 2019; 14: e0219126 (IGR: 20-3)


80538 An Examination of the Frequency of Paravascular Defects and Epiretinal Membranes in Eyes With Early Glaucoma Using En-face Slab OCT Images
Mavrommatis MA
Journal of Glaucoma 2019; 28: 265-269 (IGR: 20-3)


80774 Comparison of Spectralis and Cirrus spectral domain optical coherence tomography for the objective morphometric assessment of the neuroretinal rim width
Mitsch C
Graefe's Archive for Clinical and Experimental Ophthalmology 2019; 257: 1265-1275 (IGR: 20-3)