Retinal Disease Identification by Segmentation Techniques in Diabetic Retinopathy

Abstract

Detection of microaneurysms before diabetes increases is an essential stage in diabetic retinopathy (DR) which damages the eye, so it is big medical problem. A need arises to detect it at an early stage. It is not showing any symptoms, so it can only be a diagnosed by oculist. This paper presents the study and review of various techniques used in detection of microaneurysms as well as new approach to increasing sensitivity and reducing computational time for detection and classification of microaneurysms from the diabetic retinopathy images. This new strategy to detect MAs is based on (1) Elimination of nonuniform part of an image and standardize grayscale content of original image. (2) Performed Morphological operations for detection of Region of Interest (ROI) and elimination of blood vessels. (3) To identify real MAs two features extracted where one feature of shape which discriminates normal eye image and abnormal eye image and second feature of texture. So, this increases sensitivity and also availability. So for this whole process of new technique used publically available database called DiaretDB1 database. (4) To discriminate normal and abnormal images different clustering algorithm used.