Detection of Optic Disc Localization from Retinal Fundus Image Using Optimized Color Space

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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.authorToptas, Murat
dc.contributor.authorHanbay, Davut
dc.date.accessioned2024-08-04T20:51:35Z
dc.date.available2024-08-04T20:51:35Z
dc.date.issued2022
dc.departmentİnönü Üniversitesien_US
dc.description.abstractOptic disc localization offers an important clue in detecting other retinal components such as the macula, fovea, and retinal vessels. With the correct detection of this area, sudden vision loss caused by diseases such as age-related macular degeneration and diabetic retinopathy can be prevented. Therefore, there is an increase in computer-aided diagnosis systems in this field. In this paper, an automated method for detecting optic disc localization is proposed. In the proposed method, the fundus images are moved from RGB color space to a new color space by using an artificial bee colony algorithm. In the new color space, the localization of the optical disc is clearer than in the RGB color space. In this method, a matrix called the feature matrix is created. This matrix is obtained from the color pixel values of the image patches containing the optical disc and the image patches not containing the optical disc. Then, the conversion matrix is created. The initial values of this matrix are randomly determined. These two matrices are processed in the artificial bee colony algorithm. Ultimately, the conversion matrix becomes optimal and is applied over the original fundus images. Thus, the images are moved to the new color space. Thresholding is applied to these images, and the optic disc localization is obtained. The success rate of the proposed method has been tested on three general datasets. The accuracy success rate for the DRIVE, DRIONS, and MESSIDOR datasets, respectively, is 100%, 96.37%, and 94.42% for the proposed method.en_US
dc.identifier.doi10.1007/s10278-021-00566-8
dc.identifier.endpage319en_US
dc.identifier.issn0897-1889
dc.identifier.issn1618-727X
dc.identifier.issue2en_US
dc.identifier.pmid35018540en_US
dc.identifier.scopus2-s2.0-85122704613en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage302en_US
dc.identifier.urihttps://doi.org/10.1007/s10278-021-00566-8
dc.identifier.urihttps://hdl.handle.net/11616/100407
dc.identifier.volume35en_US
dc.identifier.wosWOS:000741249100002en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofJournal of Digital Imagingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial bee colonyen_US
dc.subjectFundus imageen_US
dc.subjectOptic disc localizationen_US
dc.subjectEigenvalueen_US
dc.titleDetection of Optic Disc Localization from Retinal Fundus Image Using Optimized Color Spaceen_US
dc.typeArticleen_US

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