Prediction of prostate tumour hypoxia using pre-treatment MRI-derived radiomics: preliminary findings

Zhong, J orcid.org/0000-0001-5325-3739, Frood, R, McWilliam, A et al. (11 more authors) (2023) Prediction of prostate tumour hypoxia using pre-treatment MRI-derived radiomics: preliminary findings. La Radiologia Medica, 128. pp. 765-774. ISSN 0033-8362

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Item Type: Article
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© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Keywords: Prostate cancer; Hypoxia; MRI; Radiomics; Radiogenomics; Machine learning
Dates:
  • Published: June 2023
  • Published (online): 17 May 2023
  • Accepted: 26 April 2023
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Biomed & Clin Sciences (LIBACS) (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 25 May 2023 09:30
Last Modified: 19 Jul 2023 08:45
Published Version: https://link.springer.com/article/10.1007/s11547-0...
Status: Published
Publisher: Springer
Identification Number: 10.1007/s11547-023-01644-3
Open Archives Initiative ID (OAI ID):

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