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dc.contributor.authorKurz, Alexander
dc.contributor.authorKrahl, Dieter
dc.contributor.authorKutzner, Heinz
dc.contributor.authorBarnhill, Raymond
dc.contributor.authorPerasole, Antonio
dc.contributor.authorFernandez Figueras, Maria Teresa
dc.contributor.authorFerrara, Gerardo
dc.contributor.authorBraun, Stephan A.
dc.contributor.authorStarz, Hans
dc.contributor.authorLlamas-Velasco, Mar
dc.contributor.authorSven Utikal, Jochen
dc.contributor.authorFröhling, Stefan
dc.contributor.authorvon Kalle, Christof
dc.contributor.authorKather, Jakob Nikolas
dc.contributor.authorSchneider, Lucas
dc.contributor.authorBrinker, Titus J.
dc.date.accessioned2023-11-07T16:17:22Z
dc.date.available2023-11-07T16:17:22Z
dc.date.issued2023
dc.identifier.citationKurz, Alexander; Krahl, Dieter; Kutzner, Heinz [et al.]. A 3-dimensional histology computer model of malignant melanoma and its implications for digital pathology. European Journal of Cancer, 2023, 193, 113294. Disponible en: <https://www.ejcancer.com/article/S0959-8049(23)00396-9/fulltext>. Fecha de acceso: 7 nov. 2023. DOI: 10.1016/j.ejca.2023.113294ca
dc.identifier.issn0959-8049ca
dc.identifier.urihttp://hdl.handle.net/20.500.12328/3861
dc.description.abstractBackground: Historically, cancer diagnoses have been made by pathologists using two-dimensional histological slides. However, with the advent of digital pathology and artificial intelligence, slides are being digitised, providing new opportunities to integrate their information. Since nature is 3-dimensional (3D), it seems intuitive to digitally reassemble the 3D structure for diagnosis. Objective: To develop the first human-3D-melanoma-histology-model with full data and code availability. Further, to evaluate the 3D-simulation together with experienced pathologists in the field and discuss the implications of digital 3D-models for the future of digital pathology. Methods: A malignant melanoma of the skin was digitised via 3 µm cuts by a slide scanner; an open-source software was then leveraged to construct the 3D model. A total of nine pathologists from four different countries with at least 10 years of experience in the histologic diagnosis of melanoma tested the model and discussed their experiences as well as implications for future pathology. Results: We successfully constructed and tested the first 3D-model of human melanoma. Based on testing, 88.9% of pathologists believe that the technology is likely to enter routine pathology within the next 10 years; advantages include a better reflectance of anatomy, 3D assessment of symmetry and the opportunity to simultaneously evaluate different tissue levels at the same time; limitations include the high consumption of tissue and a yet inferior resolution due to computational limitations. Conclusions: 3D-histology-models are promising for digital pathology of cancer and melanoma specifically, however, there are yet limitations which need to be carefully addressed.en
dc.format.extent7ca
dc.language.isoengca
dc.publisherElsevierca
dc.relation.ispartofEuropean Journal of Cancerca
dc.relation.ispartofseries193
dc.rights© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.otherDermatologiaca
dc.subject.otherPatologia digitalca
dc.subject.otherDermatopatologiaca
dc.subject.otherMelanomaca
dc.subject.otherIntel·ligència artificialca
dc.subject.otherAprenentatge profundca
dc.subject.otherDermatologíaes
dc.subject.otherPatología digitales
dc.subject.otherDermatopatologíaes
dc.subject.otherMelanomaes
dc.subject.otherInteligencia artificiales
dc.subject.otherAprendizaje profundoes
dc.subject.otherDermatologyen
dc.subject.otherDigital pathologyen
dc.subject.otherDermatopathologyen
dc.subject.otherMelanomaen
dc.subject.otherArtificial intelligenceen
dc.subject.otherDeep learningen
dc.titleA 3-dimensional histology computer model of malignant melanoma and its implications for digital pathologyen
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/publishedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapca
dc.subject.udc61ca
dc.subject.udc616.5ca
dc.identifier.doihttps://dx.doi.org/10.1016/j.ejca.2023.113294ca


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© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/
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