Review of automated diagnosis of diabetic retinopathy using the support vector machine

The automated analysis of human eye fundus image is an important task. Diabetes is a disease which occurs when the pancreas does not secrete enough insulin or the body is unable to process it properly. This disease affects slowly the circulatory system including that of the retina. As diabetes progresses, the vision of a patient may start to deteriorate and lead to diabetic retinopathy. The main stages of diabetic retinopathy are nonproliferative diabetic retinopathy(NPDR) and proliferative retinopathy(PDR). In this paper, we have proposed a computer based approach for the detection of diabetic retinopathy stages using color fundus images. The features are extracted from the raw image, using the image processing techniques and fed to the support vector machine (SVM) for classification. The results showed a sensitivity of 99.45% for the classifier and specificity of 100%.