Separation of arteries and veins in retinal fundus images with a new CNN architecture

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dc.authoridTOPTAŞ, Buket/0000-0003-2556-8199
dc.authoridHanbay, Davut/0000-0003-2271-7865
dc.authorwosidTOPTAŞ, Buket/HTL-3938-2023
dc.authorwosidHanbay, Davut/AAG-8511-2019
dc.contributor.authorToptas, Buket
dc.contributor.authorHanbay, Davut
dc.date.accessioned2024-08-04T20:53:12Z
dc.date.available2024-08-04T20:53:12Z
dc.date.issued2023
dc.departmentİnönü Üniversitesien_US
dc.description.abstractRetinal blood vessels are directly or indirectly associated with many diseases. The retinal blood vessels consist of artery and vein vessels. With the automatic correct identification of these vessels, many diseases can be prevented. In this paper, a method is proposed to separate between arteries and veins on retinal blood vessel images. In the proposed method, firstly, the image preprocessing step is applied. Then, image patches are obtained from pre-processed retinal fundus images. These patches are prepared as input to the deep learning network architecture. The proposed deep learning network architecture is presented as a new CNN architecture. This architecture decides whether the blood vessel pixels in the fundus image are arteries or veins. The proposed method was evaluated on publicly available given DRIVE, INSPIRE datasets, and the recently created LES-AV dataset. The performance of the proposed method was evaluated by using the most commonly used sensitivity, specificity, and accuracy performance measures. The accuracy measure for all vessel pixels is 0.9110 for DRIVE, 0.9654 for INSPIRE, and 0.9531 for LES-AV dataset. The proposed method is compared with other state-of-the-art artery/vein separation methods. The experimental results of the proposed method are promising. This method is suitable for automatic artery/vein separation.en_US
dc.identifier.doi10.1080/21681163.2022.2151066
dc.identifier.endpage1522en_US
dc.identifier.issn2168-1163
dc.identifier.issn2168-1171
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85143220372en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1512en_US
dc.identifier.urihttps://doi.org/10.1080/21681163.2022.2151066
dc.identifier.urihttps://hdl.handle.net/11616/101030
dc.identifier.volume11en_US
dc.identifier.wosWOS:000892024600001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofComputer Methods in Biomechanics and Biomedical Engineering-Imaging and Visualizationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFundus imageen_US
dc.subjectartery and veinen_US
dc.subjectretinal blood vesselsen_US
dc.subjectcnnen_US
dc.titleSeparation of arteries and veins in retinal fundus images with a new CNN architectureen_US
dc.typeArticleen_US

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