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Automatic Detection of Diabetic Retinopathy in Non-dilated RGB Retinal Fundus Images

by Sujithkumar S B, Vipula Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 19
Year of Publication: 2012
Authors: Sujithkumar S B, Vipula Singh
10.5120/7297-0511

Sujithkumar S B, Vipula Singh . Automatic Detection of Diabetic Retinopathy in Non-dilated RGB Retinal Fundus Images. International Journal of Computer Applications. 47, 19 ( June 2012), 26-32. DOI=10.5120/7297-0511

@article{ 10.5120/7297-0511,
author = { Sujithkumar S B, Vipula Singh },
title = { Automatic Detection of Diabetic Retinopathy in Non-dilated RGB Retinal Fundus Images },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 19 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 26-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume47/number19/7297-0511/ },
doi = { 10.5120/7297-0511 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:42:18.776044+05:30
%A Sujithkumar S B
%A Vipula Singh
%T Automatic Detection of Diabetic Retinopathy in Non-dilated RGB Retinal Fundus Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 19
%P 26-32
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a method for automatic detection of microaneurysms in digital eye fundus image is described. To develop an automated diabetic retinopathy screening system, a detection of dark lesions in digital fundus photographs is needed. Microaneurysms are the first clinical sign of diabetic retinopathy and they appear small red dots on retinal fundus images. The number of microaneurysms is used to indicate the severity of the disease. Early microaneurysm detection can help reduce the incidence of blindness. Here, we have discussed a method for the automatic detection of Diabetic Retinopathy (ADDR) in color fundus images. Different preprocessing, feature extraction and classification algorithms are used. The performance of the automated system is assessed based on Sensitivity and Specificity. The Sensitivity and Specificity of this approach are 94. 44 % and 87. 5 %, respectively.

References
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  31. University of LINCOLN, United Kingdom has released some retinal fundus images and the URL is http://reviewdb. lincoln. ac. uk/REVIEWDB/Download. aspx
Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Retinopathy Microaneurysms Fundus Image Sensitivity Specificity

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