IDENTIFICATION OF GLAUCOMA IN HUMAN FUNDUS IMAGES USING MULTI LEVEL DEEP CONVOLUTIONAL NEURAL NETWORK

Abstract

Retinal image analysis is an emerging research field in ophthalmological diseases. One of the leading ophthalmological diseases is glaucoma. Glaucoma is the leading cause for blindness. It affects the optic nerve of our eye. Due to its complexity and silent nature, early detection of this disease makes it hard to detect .In this article, we introduced convolutional neural networks in the deep learning field for the detection of glaucoma. Firstly, the fundus image of both healthy image and glaucoma image are collected with good lighting conditions,Then the CDR value for the image is obtained.Based on the CDR values obtained the result will be generated. Keywords: CNN model, Glaucoma Detection, Image Segmentation, Cup Disk Ratio, Classification .