Automated Detection and Classification of Diabetic Retinopathy and Diabetic Macular Edema in Retinal Fundus Images Using Deep Learning Approach

Abstract

Diabetics Retinopathy(DR) and Diabetics Macular Edema(DME) are the main eye diseases that should be identified earlier for preventing loss of vision.  The proposed work mainly addresses these kinds of defects with different levels of classification using Convolution Neural Network (CNN). Many researchers proved that CNN achieves better performance for computer vision-based images and the CNN, recently has a wider scope in the medical field.  Our proposed model consists of a convolution layer, pooling layer, and dense layer and classifies these DR and DME diseases with better accuracy.