A Deep Learning Method for the detection of Diabetic Retinopathy

Many Diabetic patients suffer from a medical condition in the retina of the eye known as Diabetic Retinopathy. The main cause of Diabetic Retinopathy is high blood sugar levels over a long period of time in the retina known as Diabetes Mellitus. The primary goal is to automatically classify patients having diabetic retinopathy and not having the same, given any High-Resolution Fundus Image of the Retina. For that an initial image processing has been done on the images which includes mainly, conversion of coloured (RGB) images into perfect greyscale and resizing it. Then, a Deep Learning Approach is applied in which the processed image is fed into a Convolutional Neural Network to predict whether the patient is diabetic or not. This methodology is applied on a dataset of 30 High Resolution Fundus Images of the retina. The results, so obtained are a 100 % predictive accuracy and a Sensitivity of 100 % also. Such an Automated System can easily classify images of the retina among Diabetic and Healthy patients, reducing the number of reviews of doctors.