Detection of Diabetic Retinopathy from Fundus Images using Deep Learning:A Review (original) (raw)

Diabetic retinopathy is a human eye disease observed in people having diabetics. It is caused due to damage internally in the retinal blood vessels of the light sensitive tissue at the back of the eye (retina). Effective treatment of DR (Diabetic Retinopathy) can be done if it is detected early. DR detection in early stages prevents the blindness or losing vision of the eye. Many physical tests are also available for detection but are very time consuming. One of the solutions to detect DR is CNN (Convolutional Neural Network) algorithm of deep learning. In this paper, we have performed a comparative study of CNN architectures to detect the DR. There are five stages of DR. To detect the disorders and monitoring their changes over time, fundus camera is used for capturing the fundus images which provide colored images of the interior surface of the eye. This algorithm will give the required accuracy suitable and precise for detection.