CLASSIFICATION OF RETINAL FUNDUS IMAGES USING DEEP LEARNING FOR EARLY DETECTION OF DIABETIC RETINOPATHY

Abstract

Diabetic Retinopathy is an issue of diabetes mellitus, which leads to progressive damage and even blindness of the retina. Its early detection and medication are important in order to prevent the retina’s degradation and damage. With the advances in deep learning, techniques have been applied rapidly and widely in the field of medical. Image analysis is becoming a better way to advance ophthalmology. This approach utilizes accurate visual analysis to identify the abnormality of blood vessels with improved performance over manual procedures. Employing computational approaches for the respective purpose would help in accurate retinal analysis. The proposed system includes classification of retinal fundus images into its Diabetic Retinopathy grades for early detection of Diabetic Retinopathy.