Detection of diabetic retinopathy using image processing
Master of Science in Computer Science
Faculty / School
Faculty of Computer Sciences (FCS)
Department of Computer Science
Date of Award
Dr. Muhammad Sarim
Committee Member 1
Dr. Muhammad Sarim, Supervisor, Department of Computer Science, Institute of Business Administration (IBA), Karachi
MSCS Survey Report
Diabetic retinopathy, Diabetic, Techniques.
Abstract / Summary
There are various methods used in past years for detection of Diabetic Retinopathy. Techniques discussed in this report are founded on Image Processing for identification and Machine Learning for classification for identified object. Different methods of feature extraction in funds images discussed in this paper includes vessel tracking, matched filtering and pixel classification. Whereas for identification and classification of DR based lesions and objects includes Mathematical Morphology, Region Growing, clustering and pixel-based classification. Classification Algorithm mainly used are ANN, FCM and KNN. Above methods are used in detection of multiple abnormalities due to DR which includes Exudates, Microaneurysms (MA) and Hemorrhages (HA).
Nazir, M. A. (2018). Detection of diabetic retinopathy using image processing (Unpublished survey report). Retrieved from https://ir.iba.edu.pk/research-projects/58
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