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Reseach Article

Computerised Retinal Image Analysis to Detect and Quantify Exudates Associated with Diabetic Retinopathy

by M. Ponni Bala, S. Vijayachitra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 2
Year of Publication: 2012
Authors: M. Ponni Bala, S. Vijayachitra
10.5120/8536-2077

M. Ponni Bala, S. Vijayachitra . Computerised Retinal Image Analysis to Detect and Quantify Exudates Associated with Diabetic Retinopathy. International Journal of Computer Applications. 54, 2 ( September 2012), 7-12. DOI=10.5120/8536-2077

@article{ 10.5120/8536-2077,
author = { M. Ponni Bala, S. Vijayachitra },
title = { Computerised Retinal Image Analysis to Detect and Quantify Exudates Associated with Diabetic Retinopathy },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 2 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number2/8536-2077/ },
doi = { 10.5120/8536-2077 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:38.515389+05:30
%A M. Ponni Bala
%A S. Vijayachitra
%T Computerised Retinal Image Analysis to Detect and Quantify Exudates Associated with Diabetic Retinopathy
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 2
%P 7-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the greatest concern and immediate challenges to the current health care is the severe progression of diabetes. Diabetic retinopathy is an eye disease that associated with long-standing diabetes. The conventional method followed by ophthalmogists is the regular supervision of the retina. As this method takes time and energy of the ophthalmogists, a new feature based automated technique for classification and detection of exudates in color fundus image is proposed in this paper. This method reduces the professionals work to examine on every fundus image rather than only on abnormal image. The exudates are separated from the fundus image by thresholding and removal of optic disk using morphological operation and connected component analysis. Finally, an automated Fuzzy Inference System (FIS) is used for classifying the retinal images as exudates and its severity and non-exudates. The sensitivity, specificity and accuracy are reported as 91. 11%, 100 % and 93. 84% for Fuzzy Inference System Classification.

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Index Terms

Computer Science
Information Sciences

Keywords

Exudates Fundus image connected component Morphological operation Fuzzy Inference System