{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:14:08Z","timestamp":1760058848534,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,4,30]],"date-time":"2025-04-30T00:00:00Z","timestamp":1745971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"National Funds through the Portuguese funding agency, FCT\u2014Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["2022.12385.BD"],"award-info":[{"award-number":["2022.12385.BD"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"name":"IMP Diagnostics","award":["2022.12385.BD"],"award-info":[{"award-number":["2022.12385.BD"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the high variability in Hematoxylin and Eosin (H&amp;E)-stained Whole Slide Images (WSIs), hidden stratification, and batch effects, generalizing beyond the training distribution is one of the main challenges in Deep Learning (DL) for Computational Pathology (CPath). But although DL depends on large volumes of diverse and annotated data, it is common to have a significant number of annotated samples from one or multiple source distributions, and another partially annotated or unlabeled dataset representing a target distribution for which we want to generalize, the so-called Domain Adaptation (DA). In this work, we focus on the task of generalizing from a single source distribution to a target domain. As it is still not clear which domain adaptation strategy is best suited for CPath, we evaluate three different DA strategies, namely FixMatch, CycleGAN, and a self-supervised feature extractor, and show that DA is still a challenge in CPath.<\/jats:p>","DOI":"10.3390\/s25092856","type":"journal-article","created":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T09:16:12Z","timestamp":1746090972000},"page":"2856","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Bridging Domain Gaps in Computational Pathology: A Comparative Study of Adaptation Strategies"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8003-7126","authenticated-orcid":false,"given":"Jo\u00e3o D.","family":"Nunes","sequence":"first","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal"},{"name":"Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9551-4589","authenticated-orcid":false,"given":"Diana","family":"Montezuma","sequence":"additional","affiliation":[{"name":"IMP Diagnostics, 4150-146 Porto, Portugal"},{"name":"Cancer Biology and Epigenetics Group, Research Center of Portuguese Oncology Institute of Porto\/RISE@Research Center of Portuguese Oncology Institute of Porto (Health Research Network), Portuguese Oncology Institute of Porto\/Porto Comprehensive Cancer Centre Raquel Seruca, R. Dr. Ant\u00f3nio Bernardino de Almeida, 4200-072 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7491-0873","authenticated-orcid":false,"given":"Domingos","family":"Oliveira","sequence":"additional","affiliation":[{"name":"IMP Diagnostics, 4150-146 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1681-2436","authenticated-orcid":false,"given":"Tania","family":"Pereira","sequence":"additional","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal"},{"name":"FCTUC\u2014Faculty of Sciences and Technology, University of Coimbra, 3004-516 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6741-3000","authenticated-orcid":false,"given":"Inti","family":"Zlobec","sequence":"additional","affiliation":[{"name":"Institute of Tissue Medicine and Pathology, University of Bern, 3008 Bern, Switzerland"}]},{"given":"Isabel Macedo","family":"Pinto","sequence":"additional","affiliation":[{"name":"IMP Diagnostics, 4150-146 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3760-2473","authenticated-orcid":false,"given":"Jaime S.","family":"Cardoso","sequence":"additional","affiliation":[{"name":"Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal"},{"name":"Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102885","DOI":"10.1016\/j.media.2023.102885","article-title":"An aggregation of aggregation methods in computational pathology","volume":"88","author":"Bilal","year":"2023","journal-title":"Med. 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