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Reseach Article

Auto-detection of Longitudinal Changes in Retinal Images for Monitoring Diabetic Retinopathy

by Deepali A. Godse, Dattatraya S. Bormane
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 1
Year of Publication: 2013
Authors: Deepali A. Godse, Dattatraya S. Bormane
10.5120/13359-0952

Deepali A. Godse, Dattatraya S. Bormane . Auto-detection of Longitudinal Changes in Retinal Images for Monitoring Diabetic Retinopathy. International Journal of Computer Applications. 77, 1 ( September 2013), 26-32. DOI=10.5120/13359-0952

@article{ 10.5120/13359-0952,
author = { Deepali A. Godse, Dattatraya S. Bormane },
title = { Auto-detection of Longitudinal Changes in Retinal Images for Monitoring Diabetic Retinopathy },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 1 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 26-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number1/13359-0952/ },
doi = { 10.5120/13359-0952 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:49:08.489774+05:30
%A Deepali A. Godse
%A Dattatraya S. Bormane
%T Auto-detection of Longitudinal Changes in Retinal Images for Monitoring Diabetic Retinopathy
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 1
%P 26-32
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A computer-aided retinal image analysis could provide an immediate detection and monitoring of abnormalities present in the retinal image. It allows to diagnose some retinal diseases prior to specialist inspection. This paper presents automatic system which can aid in the detection and monitoring of diabetic retinopathy (DR). The method proposed here is based on the preliminary automatic registration of retinal images, and the detection of changes in retinal images. This is done by comparing the registered retinal images. A novel algorithm is developed to achieve accurate registration. It ensures that the detected changes reflect only the real changes, and avoids any artifacts associated with the registration procedure itself. The special facts about retinal images are considered while performing image differencing. The present work in this paper is motivated by the need for automated, objective, quantitative approaches to detect the appearance of lesions and to detect longitudinal changes for monitoring DR. This system will considerably reduce the overall workload of ophthalmologists.

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Index Terms

Computer Science
Information Sciences

Keywords

Diabetic retinopathy lesions longitudinal registration retinal images