An Effective Diagnosis of Diabetic Retinopathy with Aid of Soft Computing Approaches

Abstract

DR (diabetic retinopathy) is a most probable reason of blindness in adults, but the only remedy or escape from blindness is that we have to detect DR as early. Several automated screening techniques are used to detect individual lesions in the retina. Still it takes more dependency of time and experts. To overcome those problems and also automatically detect DR in easier and faster way, we took into soft computing approaches in our proposed work. Our proposed work will discuss several amounts of soft computing algorithms, it can detect DR features (landmark and retinal lesions) in an easy manner. Processes includes are: (1) Pre-processing; (2) Optic disc localization and segmentation; (3) Localization of fovea; (4) Blood vessel segmentation; (5) Feature extraction; (6) Feature selection; Finally (7) detection of diabetic retinopathy stages (mild, moderate, severe and PDR). Our experimental results based on Matlab simulation and it takes databases of STARE and DRIVE. Proposed effective soft computing approaches should improve the sensitivity, specificity and accuracy.