A whole-slide image grading benchmark and tissue classification for cervical cancer precursor lesions with inter-observer variability

dc.contributor.authorAlbayrak, Abdulkadir
dc.contributor.authorÜnlü Akhan, Aslı
dc.contributor.authorÇalık, Nurullah
dc.contributor.authorÇapar, Abdulkerim
dc.contributor.authorBilgin, Gökhan
dc.contributor.authorTöreyin, Behçet Uğur
dc.contributor.authorMüezzinoğlu, Bahar
dc.contributor.authorTürkmen, İlknur
dc.contributor.authorDurak Ata, Lütfiye
dc.date.accessioned2021-08-05T07:23:29Z
dc.date.available2021-08-05T07:23:29Z
dc.date.issued2021
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Cerrahi Tıp Bilimleri Bölümü, Tıbbi Patoloji Ana Bilim Dalı
dc.description.abstracthe cervical cancer developing from the precancerous lesions caused by the human papillomavirus (HPV) has been one of the preventable cancers with the help of periodic screening. Cervical intraepithelial neoplasia (CIN) and squamous intraepithelial lesion (SIL) are two types of grading conventions widely accepted by pathologists. On the other hand, inter-observer variability is an important issue for final diagnosis. In this paper, a whole-slide image grading benchmark for cervical cancer precursor lesions is created and the “Uterine Cervical Cancer Database” introduced in this article is the first publicly available cervical tissue microscopy image dataset. In addition, a morphological feature representing the angle between the basal membrane (BM) and the major axis of each nucleus in the tissue is proposed. The presence of papillae of the cervical epithelium and overlapping cell problems are also discussed. Besides that, the inter-observer variability is also evaluated by thorough comparisons among decisions of pathologists, as well as the final diagnosis. [Figure not available: see fulltext.].
dc.description.sponsorshipIstanbul Technical University ; Yildiz Technical Universityen_US
dc.identifier.citationAlbayrak, A., Ünlü Akhan, A., Çalık, N., Çapar, A., Bilgin, G., Töreyin, B. U. ... Durak Ata, L. (2021). A whole-slide image grading benchmark and tissue classification for cervical cancer precursor lesions with inter-observer variability. Medical and Biological Engineering and Computing, 59(7-8), 1545-1561. https://dx.doi.org/10.1007/s11517-021-02388-w
dc.identifier.doi10.1007/s11517-021-02388-w
dc.identifier.endpage1561
dc.identifier.issn0140-0118
dc.identifier.issn1741-0444
dc.identifier.issue45511
dc.identifier.scopusqualityQ2
dc.identifier.startpage1545
dc.identifier.urihttps://dx.doi.org/10.1007/s11517-021-02388-w
dc.identifier.urihttps://hdl.handle.net/20.500.12511/7681
dc.identifier.volume59
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofMedical and Biological Engineering and Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectCervical Cancer
dc.subjectCervical Intraepithelial Neoplasia (CIN)
dc.subjectDigital Pathology
dc.subjectHistopathological Images
dc.subjectHuman Papillomavirus
dc.subjectInter-Observer Variability
dc.subjectMorphological Features
dc.subjectSquamous Intraepithelial Lesion (SIL)
dc.subjectWhole-Slide Imaging
dc.titleA whole-slide image grading benchmark and tissue classification for cervical cancer precursor lesions with inter-observer variability
dc.typeArticle

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