Optic disc and optic cup segmentation from retinal images using hybrid approach

In the present scenario, humans are surrounded by numerous diseases which affect their lifestyles. One such condition is glaucoma which originates due to sudden stress in the eye, generally termed as intraocular pressure culminating in the affliction of the optic nerve and permanent loss of vision. It is the second highest characteristic root of blindness. The optic nerve is liable for a transference of visual details to the brain from retina leading one to locate the exterior world. Clinical diagnosis of glaucoma includes an examination of the optic cup, optic disc and measurement of intraocular pressure by tonometer, pachymetry, etc. All these tasks are manual and time-consuming hence, a computer-aided diagnosis (CAD) system is needed for evaluation of glaucoma which can be done by analysis of optic disc and optic cup present in retinal fundus images using image processing approaches. Here, optic disc represents the entrance of optic nerve and site from where retinal nerve cells approach towards each other while, the optic cup is the centric depression of irregular size residing on the disc. In this work, a Level Set Based Adaptively Regularized Kernel-Based Intuitionistic Fuzzy C means (LARKIFCM) based approach is proposed for segmentation of optic disc and optic cup in retinal fundus images with improved performance for accurate diagnosis. (C) 2019 Elsevier Ltd. All rights reserved.