CUP and DISC OPTIC Segmentation Using Optimized Superpixel Classification for Glaucoma Screening

Abstract

Glaucoma, an incurable disease related to eyes which results in loss of the vision. Identifying this disease within in a proper period of time is most important, since it cannot be cured. The important aspect of this paper is to detect glaucoma at initial stages. Segmentation in the optic disc necessitates the differentiation of each super pixel by employing Histograms, centre surround statistics. Information location in merged with the above methods in increasing the performance of optic cup segmentation. Optic disc and optic cups are employed to evaluate cup to disc ratio of the disease identified. Neural network is used to extract the patterns and also to detect glaucomatous cells that are too complex to be noticed by either humans or other computer techniques.