Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

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dc.authoridSEN, BAHA/0000-0003-3577-2548
dc.authoridAKYOL, KEMAL/0000-0002-2272-5243
dc.authoridBAYIR, Safak/0000-0003-4719-8088
dc.contributor.authorAkyol, Kemal
dc.contributor.authorSen, Baha
dc.contributor.authorBayir, Safak
dc.date.accessioned2024-09-29T16:04:52Z
dc.date.available2024-09-29T16:04:52Z
dc.date.issued2016
dc.departmentKarabük Üniversitesien_US
dc.description.abstractWith the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC.en_US
dc.identifier.doi10.1155/2016/6814791
dc.identifier.issn1748-670X
dc.identifier.issn1748-6718
dc.identifier.pmid27110272en_US
dc.identifier.scopus2-s2.0-84971373709en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1155/2016/6814791
dc.identifier.urihttps://hdl.handle.net/20.500.14619/6373
dc.identifier.volume2016en_US
dc.identifier.wosWOS:000374018400001en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherHindawi Ltden_US
dc.relation.ispartofComputational and Mathematical Methods in Medicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectLocalizationen_US
dc.titleAutomatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniquesen_US
dc.typeArticleen_US

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