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A Novel Method for Micro aneurysm Detection and Diabetic Retinopathy Diagnosis

Published on December 2013 by Adarsh. P, D. Jeyakumari
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International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences
Foundation of Computer Science USA
ICIIIOES - Number 6
December 2013
Authors: Adarsh. P, D. Jeyakumari
fd1129e8-3133-439a-b9b0-abbe497e3911

Adarsh. P, D. Jeyakumari . A Novel Method for Micro aneurysm Detection and Diabetic Retinopathy Diagnosis. International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences. ICIIIOES, 6 (December 2013), 42-46.

@article{
author = { Adarsh. P, D. Jeyakumari },
title = { A Novel Method for Micro aneurysm Detection and Diabetic Retinopathy Diagnosis },
journal = { International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences },
issue_date = { December 2013 },
volume = { ICIIIOES },
number = { 6 },
month = { December },
year = { 2013 },
issn = 0975-8887,
pages = { 42-46 },
numpages = 5,
url = { /proceedings/iciiioes/number6/14324-1585/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences
%A Adarsh. P
%A D. Jeyakumari
%T A Novel Method for Micro aneurysm Detection and Diabetic Retinopathy Diagnosis
%J International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences
%@ 0975-8887
%V ICIIIOES
%N 6
%P 42-46
%D 2013
%I International Journal of Computer Applications
Abstract

In medical image processing a reliable means of microaneurysms detection in digital retinal images is still an open issue. In this paper, we propose a computerized scheme to improve microaneurysm detection. Image preprocessing is followed by the detection of microaneurysm regions using edge detection. Regions corresponding to blood vessels and bright lesions were removed by image segmentation from the fundus images. Unlike other well-known approaches of machine learning classifiers, we propose a combination of microaneurysm detection and diabetic retinopathy grading using SVM. Microaneurysm detection is decisive in diabetic retinopathy (DR) grading, so we evaluated our approach on four publicly available databases, where a promising AUC ? 0. 96 is obtained in a "normal" or "abnormal"-type classification based on the detected microaneurysms. The performance assessment of the automated system is based on Sensitivity, Specificity, and Accuracy together with the ROC curves.

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Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Retinopathy Microaneurysms Detection Svm Roc