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Decision Support System for Diagnosing Diabetic Retinopathy from Color Fundus Images

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Diabetic Retinopathy (DR) is a medical condition, also known as diabetic eye disease, which is vision-threatening damage to the retina of the eye caused by diabetes. As the technology advances, researchers are becoming more interested in intelligent medical diagnosis systems to assist screening of DR in earlier stages. In this study, variety of state-of-the-art procedures are used to extract the anatomic segments and lesions from the color fundus images. In addition, an automated system is proposed for the detection of anatomic segments and lesions by grading approach to help clinical diagnosis of the DR analysis. Four publicly available databases of color fundus images and various appropriate measurement techniques are used to compare quantitatively the performance of the proposed system. The experiments conducted on DIARETDB0, DIARETDB1, STARE, and HRF data sets have proved that accuracy, sensitivity, and specificity of the proposed system are comparable or superior to state-of-the-art methods.
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Document Type: Research Article

Affiliations: Computer Engineering Department, Faculty of Engineering, Eastern Mediterranean University, Famagusta, North Cyprus, via Mersin 10, Turkey

Publication date: March 1, 2020

This article was made available online on January 20, 2020 as a Fast Track article with title: "Decision Support System for Diagnosing Diabetic Retinopathy from Color Fundus Images".

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  • The Journal of Imaging Science and Technology (JIST) is dedicated to the advancement of imaging science knowledge, the practical applications of such knowledge, and how imaging science relates to other fields of study. The pages of this journal are open to reports of new theoretical or experimental results, and to comprehensive reviews. Only original manuscripts that have not been previously published, nor currently submitted for publication elsewhere, should be submitted.

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    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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