Degree
Master of Science in Computer Science
Department
Department of Computer Science
Faculty / School
Faculty of Computer Sciences (FCS)
Date of Submission
2018-01-01
Supervisor
Dr. Muhammad Sarim, Visiting Faculty, Department of Computer Science
Document type
MSCS Survey Report
Keywords
Abstract
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).
Recommended Citation
Nazir, M. A. (2018). Detection of diabetic retinopathy using image processing (Unpublished MSCS survey report). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/survey-reports-mscs/90
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