Semantic Nuclei Segmentation with Deep Learning on Breast Pathology Images

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dc.authoridBilgin, Gokhan/0000-0002-5532-477X
dc.authoridTuran, Servet/0000-0002-7322-3091
dc.contributor.authorTuran, Sevcan
dc.contributor.authorBilgin, Gokhan
dc.date.accessioned2025-01-27T21:07:40Z
dc.date.available2025-01-27T21:07:40Z
dc.date.issued2019
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.descriptionInternational Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science (EBBT) -- APR 24-26, 2019 -- Istanbul Arel Univ, Kemal Gozukara Campus, Istanbul, TURKEY
dc.description.abstractThe methods of facilitating the workload of doctors are tried to be developed in the diagnosis of cancer. One of these procedures is the segmentation of cell nuclei in digital images obtained in the field of pathology. For the segmentation process, deep-learning can be performed with local small patches obtained from the digital image, and pixel-based systems can be developed by using semantic segmentation technique. In this study, histopathological images obtained from hematoxylin and eosin staining are used for biopsy samples taken for diagnosis of breast cancer. The studies were performed in Matlab environment by using SegNet and U-Net algorithms and the accuracy of semantic segmentation was evaluated comparatively.
dc.description.sponsorshipIEEE Turkey Sect,IEEE EMB,Erasmus+,Europass
dc.identifier.doi10.1109/ebbt.2019.8741715
dc.identifier.isbn978-1-7281-1013-4
dc.identifier.scopus2-s2.0-85068555618
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ebbt.2019.8741715
dc.identifier.urihttps://hdl.handle.net/20.500.12428/28139
dc.identifier.wosWOS:000491430200020
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2019 Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (Ebbt)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20250125
dc.subjectHistopathological images
dc.subjectnuclei segmentation
dc.subjectsemantic segmentation
dc.subjectSegNet
dc.subjectU-Net
dc.titleSemantic Nuclei Segmentation with Deep Learning on Breast Pathology Images
dc.title.alternativeMeme patolojisi görüntüleri üzerinde derin ö?renme ile semantik çekirdek bölütleme
dc.typeConference Object

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