Digital image processing software for diagnosing diabetic retinopathy from fundus photograph

Tanapat Ratanapakorn,1 Athiwath Daengphoonphol,2 Nawapak Eua-Anant,2 Yosanan Yospaiboon1 1KKU Eye Center, Department of Ophthalmology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; 2Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thaila...

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Autores principales:	Ratanapakorn T, Daengphoonphol A, Eua-Anant N, Yospaiboon Y
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2019
Materias:	Automated diabetic retinopathy software Diabetic retinopathy screening Fundus photography diagnosis Digital image processing Ophthalmology RE1-994
Acceso en línea:	https://doaj.org/article/95dd2beac15a4630803fbf518c182fd9
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spelling	oai:doaj.org-article:95dd2beac15a4630803fbf518c182fd92021-12-02T03:57:30ZDigital image processing software for diagnosing diabetic retinopathy from fundus photograph1177-5483https://doaj.org/article/95dd2beac15a4630803fbf518c182fd92019-04-01T00:00:00Zhttps://www.dovepress.com/digital-image-processing-software-for-diagnosing-diabetic-retinopathy--peer-reviewed-article-OPTHhttps://doaj.org/toc/1177-5483Tanapat Ratanapakorn,1 Athiwath Daengphoonphol,2 Nawapak Eua-Anant,2 Yosanan Yospaiboon1 1KKU Eye Center, Department of Ophthalmology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; 2Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand Objective: The aim of this study was to develop automated software for screening and diagnosing diabetic retinopathy (DR) from fundus photograph of patients with diabetes mellitus. Methods: The extraction of clinically significant features to detect pathologies of DR and the severity classification were performed by using MATLAB R2015a with MATLAB Image Processing Toolbox. In addition, the graphic user interface was developed using the MATLAB GUI Toolbox. The accuracy of software was measured by comparing the obtained results to those of the diagnosis by the ophthalmologist. Results: A set of 400 fundus images, containing 21 normal fundus images and 379 DR fundus images (162 non-proliferative DR and 217 proliferative DR), was interpreted by the ophthalmologist as a reference standard. The initial result showed that the sensitivity, specificity and accuracy of this software in detection of DR were 98%, 67% and 96.25%, respectively. However, the accuracy of this software in classifying non-proliferative and proliferative diabetic retinopathy was 66.58%. The average time for processing is 7 seconds for one fundus image.Conclusion: The automated DR screening software was developed by using MATLAB programming and yielded 96.25% accuracy for the detection of DR when compared to that of the diagnosis by the ophthalmologist. It may be a helpful tool for DR screening in the distant rural area where ophthalmologist is not available. Keywords: automated diabetic retinopathy software, diabetic retinopathy screening, fundus photography diagnosis, digital image processingRatanapakorn TDaengphoonphol AEua-Anant NYospaiboon YYospaiboon YDove Medical PressarticleAutomated diabetic retinopathy softwareDiabetic retinopathy screeningFundus photography diagnosisDigital image processingOphthalmologyRE1-994ENClinical Ophthalmology, Vol Volume 13, Pp 641-648 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Automated diabetic retinopathy software Diabetic retinopathy screening Fundus photography diagnosis Digital image processing Ophthalmology RE1-994
spellingShingle	Automated diabetic retinopathy software Diabetic retinopathy screening Fundus photography diagnosis Digital image processing Ophthalmology RE1-994 Ratanapakorn T Daengphoonphol A Eua-Anant N Yospaiboon Y Yospaiboon Y Digital image processing software for diagnosing diabetic retinopathy from fundus photograph
description	Tanapat Ratanapakorn,1 Athiwath Daengphoonphol,2 Nawapak Eua-Anant,2 Yosanan Yospaiboon1 1KKU Eye Center, Department of Ophthalmology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand; 2Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand Objective: The aim of this study was to develop automated software for screening and diagnosing diabetic retinopathy (DR) from fundus photograph of patients with diabetes mellitus. Methods: The extraction of clinically significant features to detect pathologies of DR and the severity classification were performed by using MATLAB R2015a with MATLAB Image Processing Toolbox. In addition, the graphic user interface was developed using the MATLAB GUI Toolbox. The accuracy of software was measured by comparing the obtained results to those of the diagnosis by the ophthalmologist. Results: A set of 400 fundus images, containing 21 normal fundus images and 379 DR fundus images (162 non-proliferative DR and 217 proliferative DR), was interpreted by the ophthalmologist as a reference standard. The initial result showed that the sensitivity, specificity and accuracy of this software in detection of DR were 98%, 67% and 96.25%, respectively. However, the accuracy of this software in classifying non-proliferative and proliferative diabetic retinopathy was 66.58%. The average time for processing is 7 seconds for one fundus image.Conclusion: The automated DR screening software was developed by using MATLAB programming and yielded 96.25% accuracy for the detection of DR when compared to that of the diagnosis by the ophthalmologist. It may be a helpful tool for DR screening in the distant rural area where ophthalmologist is not available. Keywords: automated diabetic retinopathy software, diabetic retinopathy screening, fundus photography diagnosis, digital image processing
format	article
author	Ratanapakorn T Daengphoonphol A Eua-Anant N Yospaiboon Y Yospaiboon Y
author_facet	Ratanapakorn T Daengphoonphol A Eua-Anant N Yospaiboon Y Yospaiboon Y
author_sort	Ratanapakorn T
title	Digital image processing software for diagnosing diabetic retinopathy from fundus photograph
title_short	Digital image processing software for diagnosing diabetic retinopathy from fundus photograph
title_full	Digital image processing software for diagnosing diabetic retinopathy from fundus photograph
title_fullStr	Digital image processing software for diagnosing diabetic retinopathy from fundus photograph
title_full_unstemmed	Digital image processing software for diagnosing diabetic retinopathy from fundus photograph
title_sort	digital image processing software for diagnosing diabetic retinopathy from fundus photograph
publisher	Dove Medical Press
publishDate	2019
url	https://doaj.org/article/95dd2beac15a4630803fbf518c182fd9
work_keys_str_mv	AT ratanapakornt digitalimageprocessingsoftwarefordiagnosingdiabeticretinopathyfromfundusphotograph AT daengphoonphola digitalimageprocessingsoftwarefordiagnosingdiabeticretinopathyfromfundusphotograph AT euaanantn digitalimageprocessingsoftwarefordiagnosingdiabeticretinopathyfromfundusphotograph AT yospaiboony digitalimageprocessingsoftwarefordiagnosingdiabeticretinopathyfromfundusphotograph AT yospaiboony digitalimageprocessingsoftwarefordiagnosingdiabeticretinopathyfromfundusphotograph
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Digital image processing software for diagnosing diabetic retinopathy from fundus photograph

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