A Software System for Grading Diabetic Retinopathy by Analyzing Retinal Images
Medical imaging is very popular and is vital in designing Computer-Aided Diagnosis (CAD) for various diseases such as tumor detection using MRI. Diabetic retinopathy is an eye disease that is caused by the increase of insulin in blood in diabetic patients. It can cause total blindness if not detected and treated in time. The disease affects human retina and shows different signs on retinal surface as time passes. In this chapter, the authors present a software based on novel algorithms for early detection of diabetic retinopathy. It detects dark (Microaneurysms, Haemorrhages) and bright (hard exudates, cotton wool spots) lesions from retinal image. The algorithms consist of retinal image preprocessing, main component extraction, detection of candidate lesions, feature extraction, and finally classification using modified m-mediods based classifier. The proposed system is evaluated using publicly available retinal image databases, and results demonstrate the validity of proposed system.