Image processing and classification in diabetic retinopathy: A review

Abstract

Diabetic retinopathy is one of the disabling microvascular complications of diabetes mellitus that causes the loss of central vision or in cases complete vision loss if not recognized and cured at the earlier stage. This work reviews the latest techniques in digital image processing and pattern classification employed for the detection of diabetic retinopathy and compares them on the basis of different performance measures like sensitivity, specificity, accuracy and area under the curve in receiver operating characteristic. The classification of diabetic retinopathy follows various steps like pre-processing, feature extraction and classification of microaneurysm, hemorrhages, exudates and cotton woolen spot. In this paper, the reported literature in each domain is analyzed.