Whole Slide Images in Artificial Intelligence Applications in Digital Pathology: Challenges and Pitfalls

Basit Öğe Kaydı
dc.authorscopusid8386828500
dc.authorscopusid57219768168
dc.authorscopusid34768054600
dc.contributor.authorBasak, Kayhan
dc.contributor.authorOzyoruk, Kutsev Bengisu
dc.contributor.authorDemir, Derya
dc.date.accessioned2024-08-25T18:38:22Z
dc.date.available2024-08-25T18:38:22Z
dc.date.issued2023
dc.departmentEge Üniversitesien_US
dc.description.abstractThe use of digitized data in pathology research is rapidly increasing. The whole slide image (WSI) is an indispensable part of the visual examination of slides in digital pathology and artificial intelligence applications; therefore, the acquisition of WSI with the highest quality is essential. Unlike the conventional routine of pathology, the digital conversion of tissue slides and the differences in its use pose difficulties for pathologists. We categorized these challenges into three groups: before, during, and after the WSI acquisition. The problems before WSI acquisition are usually related to the quality of the glass slide and reflect all existing problems in the analytical process in pathology laboratories. WSI acquisition problems are dependent on the device used to produce the final image file. They may be related to the parts of the device that create an optical image or the hardware and software that enable digitization. Post-WSI acquisition issues are related to the final image file itself, which is the final form of this data, or the software and hardware that will use this file. Because of the digital nature of the data, most of the difficulties are related to the capabilities of the hardware or software. Being aware of the challenges and pitfalls of using digital pathology and AI will make pathologists' integration to the new technologies easier in their daily practice or research.en_US
dc.identifier.doi10.5146/tjpath.2023.01601
dc.identifier.endpage108en_US
dc.identifier.issn1018-5615
dc.identifier.issn1309-5730
dc.identifier.issue2en_US
dc.identifier.pmid36951221en_US
dc.identifier.scopus2-s2.0-85159768307en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage101en_US
dc.identifier.trdizinid1177012en_US
dc.identifier.urihttps://doi.org/10.5146/tjpath.2023.01601
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1177012
dc.identifier.urihttps://hdl.handle.net/11454/100994
dc.identifier.volume39en_US
dc.identifier.wosWOS:000995762600001en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherFederation Turkish Pathology Socen_US
dc.relation.ispartofTurkish Journal of Pathologyen_US
dc.relation.publicationcategoryDiğeren_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240825_Gen_US
dc.subjectWhole slide imagesen_US
dc.subjectArtificial intelligenceen_US
dc.subjectDigital pathologyen_US
dc.subjectChallengesen_US
dc.titleWhole Slide Images in Artificial Intelligence Applications in Digital Pathology: Challenges and Pitfallsen_US
dc.typeReview Articleen_US

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