Automatic cell nuclei segmentation using superpixel and clustering methods in histopathological images

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dc.authorid0000-0002-8470-4579en_US
dc.contributor.authorMendi, Gamze
dc.contributor.authorBudak, Cafer
dc.date.accessioned2022-12-21T12:05:25Z
dc.date.available2022-12-21T12:05:25Z
dc.date.issued2021en_US
dc.departmentDicle Üniversitesi, Mühendislik Fakültesi, Biyomedikal Mühendisliği Bölümüen_US
dc.description.abstractIt is seen that there is an increase in cancer and cancer-related deaths day by day. Early diagnosis is vital for the early treatment of the cancerous area. Computer-aided programs allow for the early diagnosis of unhealthy cells that specialist pathologists diagnose due to efforts. In this study, clustering and superpixel segmentation techniques were used to detect cell nuclei in high-resolution histopathology images automatically. As a result of the study, the successful performances of the segmentation algorithms were analyzed and evaluated. It is seen that better success is obtained in the Watershed and FCM algorithms in highresolution histopathological images used. Quickshift and SLIC methods gave better results in terms of precision. It is seen that there are k-Means and FCM algorithms that provide the best performance in F measure (F-M), and the correct negative rate (TNR) is more successful in Quickshift, kMeans, and SLIC methods.en_US
dc.identifier.citationMendi, G. ve Budak, C. (2021). Automatic cell nuclei segmentation using superpixel and clustering methods in histopathological images. Balkan Journal of Electrical and Computer Engineering, 9(3), 304-309.en_US
dc.identifier.doi10.17694/bajece.864266
dc.identifier.endpage309en_US
dc.identifier.issn2147-284X
dc.identifier.issue3en_US
dc.identifier.startpage304en_US
dc.identifier.trdizinid471964
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/471964
dc.identifier.urihttps://hdl.handle.net/11468/11097
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/471964
dc.identifier.volume9en_US
dc.indekslendigikaynakTR-Dizin
dc.institutionauthorBudak, Cafer
dc.language.isoenen_US
dc.publisherBalkan Yayınen_US
dc.relation.ispartofBalkan Journal of Electrical and Computer Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSegmentationen_US
dc.subjectHistopathological image analysisen_US
dc.subjectSuperpixelsen_US
dc.subjectImage processingen_US
dc.titleAutomatic cell nuclei segmentation using superpixel and clustering methods in histopathological imagesen_US
dc.titleAutomatic cell nuclei segmentation using superpixel and clustering methods in histopathological images
dc.typeArticleen_US

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