Optic Disc and Optic Cup Segmentation Methodology for Glaucoma Detection

Abstract

A retinal image is an essential tool for ophthalmology diagnosis. It is necessary for the early detection of many retinal diseases including glaucoma. Glaucoma acquires a second place in the leading causes of blindness worldwide. It damages the optic nerve which is responsible for connecting 1.2 million different nerve fibers to the brain. Once the optic nerve is destroyed it can not be treated but its early diagnosis and treatment can prevent the vision loss. The detection of glaucoma is usually performed by measuring the ratio between the optic disc (OD) and the optic cup (OC). The average ratio between the OD and the OC is 0.3. If it is higher than 0.3, then it is an indication of glaucoma. This paper aims to present an image processing algorithm for automatic identification of glaucoma by using active contour (snake) model to contour the OD and the OC boundaries that will help calculate the cup to disk ratio (CDR). The proposed model will help ophthalmologists to monitor any changes occur in the optic nerve.