A fast approach to human retina optic disc segmentation using fuzzy c-means level set evolution

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dc.contributor.authorÇelik, Canan
dc.contributor.authorErdoğmuş, P.
dc.date.accessioned2026-03-25T14:41:36Z
dc.date.available2026-03-25T14:41:36Z
dc.date.issued2017
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractThe process of localization and segmentation of the optic disc (OD) plays a crucial role in automatic screening for eye disease. This paper presents a novel and simple iterative method for rapid, fully automatic localization and segmentation of the OD in retinal fundus images. Furthermore, this new method can find the boundary of the OD using the initial fuzzy clustering means algorithm. The proposed method employs a new level set evolution based on the fuzzy clustering algorithm. The proposed technique was compared, in terms of performance, with various methods in the literature, and the results were found to be conclusive and effective. The obtained results suggest that this OD segmentation technique is accurate in addition to being computationally inexpensive.
dc.identifier.endpage543
dc.identifier.issue1
dc.identifier.startpage555
dc.identifier.urihttps://hdl.handle.net/20.500.12684/22232
dc.identifier.volume6
dc.language.isoen
dc.publisherJournalERAS (Journal of Engineering Research and Applied Science Publishing Group)
dc.relation.ispartofJournal of Engineering Research and Applied Science
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_Yazar_20260325
dc.subjectAutomatic screening for eye disease
dc.subjectfuzzy clustering
dc.subjectlevel set method
dc.subjectoptic disc
dc.subjectlocalization
dc.subjectsegmentation
dc.titleA fast approach to human retina optic disc segmentation using fuzzy c-means level set evolution
dc.typeArticle

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