Comparative Analysis of Vision Transformers and Morphological Approaches for Ki-67 Index Estimation on Histopathologic Images: An Experimental Evaluation

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dc.contributor.authorAkdeniz, Ahmet Sezer
dc.contributor.authorOzgur, Berkan
dc.contributor.authorSahin, Emre
dc.contributor.authorKaradag, Ozge Oztimur
dc.contributor.authorGunizi, Ozlem Ceren
dc.date.accessioned2026-01-24T12:29:01Z
dc.date.available2026-01-24T12:29:01Z
dc.date.issued2024
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description32nd IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2024 -- Tarsus Univ Campus, Mersin, TURKEY
dc.description.abstractThis research comprehensively compares two different methodologies for predicting the Ki-67 index- morphological-based analysis and Vision Transformers (ViT). The morphological method focuses on the shape and structural features of tissues and cell structures. On the other hand, Vision Transformers represents an innovative approach developed through the use of attention mechanisms and transformer architectures. ViT offers a different perspective by modeling global context information in recognizing image patterns. This analysis provides a deeper understanding of the accuracy, efficiency, and applicability of current techniques in histopathological image processing, highlighting the potential to advance existing methodologies used in cancer diagnosis. This comparative study aims to evaluate the performance differences between morphological analyses and transformer-based models, identifying the most effective and reliable methods for predicting the Ki-67 index. Experimental analysis, revealed that due to the limited number of labeled data on this domain, traditional morphologic approaches are currently more promising than the vision transformers.
dc.description.sponsorshipIEEE,IEEE Turkey,Koluman & Berdan,Loodos,Figes,Turkcell,Yildirim Elect
dc.identifier.doi10.1109/SIU61531.2024.10600996
dc.identifier.isbn979-8-3503-8897-8
dc.identifier.isbn979-8-3503-8896-1
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-85200881597
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/SIU61531.2024.10600996
dc.identifier.urihttps://hdl.handle.net/20.500.12868/5070
dc.identifier.wosWOS:001297894700218
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIeee
dc.relation.ispartof32nd Ieee Signal Processing and Communications Applications Conference, Siu 2024
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260121
dc.subjectKi-67
dc.subjectViT
dc.subjectMorphology
dc.subjectSegmentation
dc.subjectCancer
dc.titleComparative Analysis of Vision Transformers and Morphological Approaches for Ki-67 Index Estimation on Histopathologic Images: An Experimental Evaluation
dc.title.alternativeHistopatolojik Görüntülerde Ki-67 İndeks Tahmini için Görüntü Dönüştürücüler ile Morfolojik Yaklaşımların Karşılaştırmalı Analizi: Deneysel Bir Değerlendirme
dc.typeConference Object

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