GLAUCOMA DISEASE DETECTION FROM RETINA SCANNED IMAGES USING NEURAL NETWORKS

An image processing technique for the detection of glaucoma which mainly affects the optic disc by increasing the cup size.During early stages it was difficult to detect Glaucoma, which is in fact second leading cause of blindness.In this paper glaucoma is categorized through extraction of features from retinal fundus images.The features include (i) Cup to Disc Ratio (CDR), which is one of the primary physiological parameter for the diagnosis of glaucoma and (ii) Ratio of Neuroretinal Rim in inferior, superior, temporal and nasal quadrants i.e. (ISNT quadrants) for verification of the ISNT rule.Using VGG16 algorithm we are going to classify the images .