Classification of Diabetic Retinopathy types based on Convolution Neural Network (CNN)

Abstract

- Diabetes mellitus have an eye disease called diabetic retinopathy. The early discovery of the disease is a great achievement in management of diabetic retinopathy. We use Fundus images are used for identification of the nature of an illness or other problem through examination of the symptoms to check for any abnormalities or any change in the retina. In this paper, Convolutional Neural Networks (CNN) is performed to classify the retinal fundus images to normal, background and pre-proliferative retinopathy. The proposed model consists of 5 convolutional layers followed by 5 max pooling layers. Finally, a global average pooling is used. In this work we achieve accuracy reached 95.23%.