Open AccessAutomatic Detection and Localization of Macular Edema
Author(s) -
S. Sumithra,
K. R. Remya,
M. N. Giri Prasad
Publication year - 2020
Publication title -
international journal of innovative science and research technology
Language(s) - English
Resource type - Journals
ISSN - 2456-2165
DOI - 10.38124/ijisrt20sep342
Subject(s) - diabetic retinopathy , macular edema , linear discriminant analysis , computer science , artificial intelligence , diabetic macular edema , retinal , cluster analysis , ophthalmology , edema , medicine , pattern recognition (psychology) , diabetes mellitus , surgery , endocrinology
Diabetic retinopathy is an eye disease and causes vision loss to the people who are suffering longer from the diabetes. Exudates, bright and red lesions are identified in the diabetic retinal eye. Automatic detection and localization of macular edema is a challenging issue since exudates have non uniform illumination and are low contrasted. Proposed algorithm to detect macular edema encompasses Simple Linear Iterative Clustering, Fisher linear discriminant and Support vector machine classifer. Optic Disc extraction prior to exudates extraction is also introduced. Performance of the proposed detection algorithm is tested on easily available databases: Diaretdb1, Messidor and E_optha Ex. Proposed method shows an accuracy of 97.81%, specificity 98.65 and Sensitivity 82.71%.