Automated detection of exudates in diabetic retinopathy patients
Master of Science in Computer Science
Faculty / School
Faculty of Computer Sciences (FCS)
Department of Computer Science
Date of Award
Dr. Muhammad Saeed.
Committee Member 1
Dr. Muhammad Saeed, Supervisor, Department of Computer Science, Institute of Business Administration (IBA), Karachi.
MSCS Survey Report
Automated Detection, Diabetic Retinopathy, Exudates
Abstract / Summary
Diabetic retinopathy affects the vision of diabetic patient due to the damage of tiny blood vessels at the back of retina. If left undiagnosed and untreated, diabetic retinopathy can result initially in mild vision problems and then, to complete blindness. Timely detection followed by suitable treatment can help many people from going through the agony of vision loss. Image processing and computer vision techniques can be used for the automatic detection of Diabetic Retinopathy. This report discusses an effective algorithm to detect and localize optical disc, blood vessels and exudates in retinal fundus images. The algorithm applies various computer vision and morphological image processing techniques to diagnose and distinguish exudates in diabetic retinopathy patients. The proposed algorithm is tested on five retinal images that were hand marked by an ophthalmologist. We obtained 82.1% predictive value and 88.9% sensitivity with our algorithm.
Iftikhar, A. (2017). Automated detection of exudates in diabetic retinopathy patients (Unpublished survey report). Retrieved from https://ir.iba.edu.pk/research-projects/63
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