A Decision Support Framework for Automated Screening of Diabetic Retinopathy

The early signs of diabetic retinopathy (DR) are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS) for automated screening of ear...

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Main Authors: P. Kahai, K. R. Namuduri, H. Thompson
Format: Article
Language:English
Published: Wiley 2006-01-01
Series:International Journal of Biomedical Imaging
Online Access:http://dx.doi.org/10.1155/IJBI/2006/45806
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author P. Kahai
K. R. Namuduri
H. Thompson
author_facet P. Kahai
K. R. Namuduri
H. Thompson
author_sort P. Kahai
collection DOAJ
description The early signs of diabetic retinopathy (DR) are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS) for automated screening of early signs of diabetic retinopathy. Classification schemes for deducing the presence or absence of DR are developed and tested. The detection rule is based on binary-hypothesis testing problem which simplifies the problem to yes/no decisions. An analysis of the performance of the Bayes optimality criteria applied to DR is also presented. The proposed DSS is evaluated on the real-world data. The results suggest that by biasing the classifier towards DR detection, it is possible to make the classifier achieve good sensitivity.
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series International Journal of Biomedical Imaging
spelling doaj-art-0d8ecd98dbf84027978ca2bb88656ae72025-02-03T06:13:48ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962006-01-01200610.1155/IJBI/2006/4580645806A Decision Support Framework for Automated Screening of Diabetic RetinopathyP. Kahai0K. R. Namuduri1H. Thompson2Department of Electrical & Computer Engineering, Wichita State University, Wichita, KS 67260-0044, USADepartment of Electrical & Computer Engineering, Wichita State University, Wichita, KS 67260-0044, USALSU Eye Center, Louisiana State University, New Orleans, LA 70112, USAThe early signs of diabetic retinopathy (DR) are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS) for automated screening of early signs of diabetic retinopathy. Classification schemes for deducing the presence or absence of DR are developed and tested. The detection rule is based on binary-hypothesis testing problem which simplifies the problem to yes/no decisions. An analysis of the performance of the Bayes optimality criteria applied to DR is also presented. The proposed DSS is evaluated on the real-world data. The results suggest that by biasing the classifier towards DR detection, it is possible to make the classifier achieve good sensitivity.http://dx.doi.org/10.1155/IJBI/2006/45806
spellingShingle P. Kahai
K. R. Namuduri
H. Thompson
A Decision Support Framework for Automated Screening of Diabetic Retinopathy
International Journal of Biomedical Imaging
title A Decision Support Framework for Automated Screening of Diabetic Retinopathy
title_full A Decision Support Framework for Automated Screening of Diabetic Retinopathy
title_fullStr A Decision Support Framework for Automated Screening of Diabetic Retinopathy
title_full_unstemmed A Decision Support Framework for Automated Screening of Diabetic Retinopathy
title_short A Decision Support Framework for Automated Screening of Diabetic Retinopathy
title_sort decision support framework for automated screening of diabetic retinopathy
url http://dx.doi.org/10.1155/IJBI/2006/45806
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