Computational methods for metastasis detection in lymph nodes and characterization of the metastasis-free lymph node microarchitecture: A systematic-narrative hybrid review

Budginaite, E., Magee, D.R. orcid.org/0000-0003-2170-3103, Kloft, M. et al. (2 more authors) (2024) Computational methods for metastasis detection in lymph nodes and characterization of the metastasis-free lymph node microarchitecture: A systematic-narrative hybrid review. Journal of Pathology Informatics, 15. 100367. ISSN 2229-5089

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Item Type: Article
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© 2024 The Authors. Published by Elsevier Inc. on behalf of Association for Pathology Informatics. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Keywords: Lymph node; Artificial intelligence; Segmentation; Immunity; Review
Dates:
  • Published: December 2024
  • Published (online): 4 February 2024
  • Accepted: 31 January 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Medical Research (LIMR) > Division of Pathology and Data Analytics
Depositing User: Symplectic Publications
Date Deposited: 15 Jul 2024 15:04
Last Modified: 15 Jul 2024 15:04
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.jpi.2024.100367
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