Abstract #81409 Published in IGR 20-3

Automated Vision-Based High Intraocular Pressure Detection Using Frontal Eye Images

Aloudat M; Faezipour M; El-Sayed A
IEEE journal of translational engineering in health and medicine 2019; 7: 3800113

Glaucoma, the silent thief of vision, is mostly caused by the gradual increase of pressure in the eye which is known as intraocular pressure (IOP). An effective way to prevent the rise in eye pressure is by early detection. Prior computer vision-based work regarding IOP relies on fundus images of the optic nerves. This paper provides a novel vision-based framework to help in the initial IOP screening using only frontal eye images. The framework first introduces the utilization of a fully convolutional neural (FCN) network on frontal eye images for sclera and iris segmentation. Using these extracted areas, six features that include mean redness level of the sclera, red area percentage, Pupil/Iris diameter ratio, and three sclera contour features (distance, area, and angle) are computed. A database of images from the Princess Basma Hospital is used in this work, containing 400 facial images; 200 cases with normal IOP; and 200 cases with high IOP. Once the features are extracted, two classifiers (support vector machine and decision tree) are applied to obtain the status of the patients in terms of IOP (normal or high). The overall accuracy of the proposed framework is over 97.75% using the decision tree. The novelties and contributions of this work include introducing a fully convolutional network architecture for eye sclera segmentation, in addition to scientifically correlating the frontal eye view (image) with IOP by introducing new sclera contour features that have not been previously introduced in the literature from frontal eye images for IOP status determination.

1Department of Computer Science and EngineeringUniversity of BridgeportBridgeportCT06604USA.

Full article


1.6 Prevention and screening (Part of: 1 General aspects)
6.1.1 Devices, techniques (Part of: 6 Clinical examination methods > 6.1 Intraocular pressure measurement; factors affecting IOP)
6.8.1 Anterior segment (Part of: 6 Clinical examination methods > 6.8 Photography)

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