research

Image-Based Risk Assessment Analysis for Glaucoma Determination

Abstract

Glaucoma is the most common cause of blindness in the world, and it is known as the silent thief of vision because it can sneak up on any patient. However, the loss of vision from Glaucoma is preventable. Glaucoma is caused by the gradual increase of pressure in the eye which is known as Intraocular Pressure (IOP). While the pressure increases in the eye, different parts of the eye become affected until the eye parts are damaged. The eye vessels' sizes are so small that they easily become affected. Moreover, the pressure inside the eye pushes the lens affecting the size of the Pupil. Also, the pressure in the eye presses the optic nerve in the back of the eye causing damage to the nerve fibers. Over 90% of Glaucoma cases have no signs or symptoms because peripheral vision can be lost before a person's central vision is affected. The only way to prevent Glaucoma is by early detection. This research study calculates three features from the frontal eye image that can be used to assess the risk of Glaucoma. These features include redness of the sclera, red area percentage, and the Pupil size. The database used in the work contains 100 facial images that have been divided into 50 healthy cases and 50 non-healthy cases with high eye pressure. Once the features were extracted, a neural network classification is applied to obtain the status of the patients in terms of eye pressure

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