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Detection and Classification of Cotton Wool Spots in Diabetic Retinopathy
Author(s) -
S. Sudha*,
A. Srinivasan,
T. Gayathri Devi
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c6805.098319
Subject(s) - cotton wool spots , diabetic retinopathy , blindness , diabetes mellitus , retinopathy , spots , segmentation , support vector machine , blood sugar , medicine , artificial intelligence , ophthalmology , computer science , pattern recognition (psychology) , optometry , pathology , endocrinology
Diabetes is a disorder that occurs when blood sugar level increases. Further increase of blood glucose lead to serious complications and it will affect major organs of our body. Diabetes affects both of the eyes called Diabetic Retinopathy (DR). If it is treated properly eye blindness can be prevented. The main objective of this paper is to detect Cotton Wool Spots (CWS) using morphological operations and the spots are segmented using k-means segmentation. Distinct features are extracted from the segmented image to train and test the Support Vector Machine (SVM) classifier. It is used to classify the lesions and the stages of diabetic retinopathy. It is noticed that sensitivity is 95% and the specificity is 86%.

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