DOI: 10.5176/2251-1679_CGAT17.21

Authors: Lakshika Nanayakkara and Nihal Kodikara


Non-proliferative Diabetic Retinopathy is a health problem which is prevalent in diabetic patients. It is caused by the expansion of untwisted blood vessels that over time, result in microaneurysms, haemorrhages, and exudates in the retina. This is the preliminary reason for visual impairment and eventual blindness in adults. These retinal anomalies can be identified using fundus images. This paper proposes a novel approach for classifying microaneurysms and exudates of Nonproliferative Diabetic Retinopathy (NPDR) patients, using digital image processing and support vector machine. The datasets used for the study were gathered from Vision Care (Pvt) Ltd, National Eye Hospital and publicly available catalogues such as DRIVE and STARE. User level evaluation conducted with 40 candidates showed a 100{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465} and 84.2{6e6090cdd558c53a8bc18225ef4499fead9160abd3419ad4f137e902b483c465} success rates for detecting NPDR retinal abnormalities and exudates respectively. In addition to that through evaluation results indicate that the proposed approach microaneurysms lesion identification yields much better accuracy than the exudates.

Keywords: Diabetic Retinopathy; Non-Proliferative Diabetic Retinopathy; Proliferative Diabetic Retinopathy; Optic Disk; Image Processing; Exudates; Microaneurysms; Support Vector Machine


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