Glaucoma Detection from Retinal Fundus Images
Rahul Krishnan, Varun Sekhar, J. Sidharth, S Gautham, G. Gopakumar
Abstract
Glaucoma is an optic nerve disease that damages the optic nerves and can cause blindness if it remains untreated. CDR (Cup-to-Disc Diameter Ratio) is one of the factors with which we can determine the presence of Glaucoma. The detection is carried out using an existing pipeline in which segmentation of optic disc and cup is carried out first followed by CDR calculation based on which a prediction is made. A threshold-based algorithm was used for segmenting the Optic Disc. For the cup region, a modified region growing algorithm was applied. The segmentations were followed by infilling blood vessels and morphological operations. The CDR value calculated from the segmented images was fed to an SVM model to classify. Cup segmentation is a challenging and hard problem. There are many algorithms that tackle the same. The proposed method approaches this challenge with a novel method for segmenting the optic cup. The results show that the proposed approach could accurately predict the presence of Glaucoma with less computational requirements.