Insight Retina: A Deep Learning Approach to Diagnose Diabetic Retinopathy

The greatest cause of blindness in the world and a frequent cause of diabetes melitus is Diabetic-Retinopathy (DR). To stop vision loss in afflicted people, early identification and decision making are essential. Diabetic - Retinopathy is a eye disorder that is currently being diagnosed manually by ophthalmologists. The diagnosis and recovery takes a great deal of time, effort and money, sometimes even a risk of misdiagnosis. Deep-learning has been the most highly emerging popular method that performs better in many fields, especially in the process analysing data and as well as classifying images from medical imaging. The IdX-DR and EyeArt AI are some existing systems that are legally approved and widely used in many places. Convolution neural networks and transfer learning are widely used as they are more effective. The dataset called Asia Pacific Tele-Ophthalmology Society (APTOS) is a large collection, which contains images acquired using Fundus Imaging and is available in open-source which is used extensively. The Insight Retina uses Contrast Limited Adaptive Histogram Equalization for enhancement of images and pre-trained model Res-Net for detection, thus providing improved performance and a reliable 0.893 Kappa accuracy score from the DR model. Insight Retina then generates a report for the input image providing accurate information about the stage of the Diabetic-Retinopathy.