Intensity standardization of MRI prior to radiomic feature extraction for artificial intelligence research in glioma-a systematic review

Fatania, K orcid.org/0000-0003-2421-1083, Mohamud, F, Clark, A et al. (5 more authors) (2022) Intensity standardization of MRI prior to radiomic feature extraction for artificial intelligence research in glioma-a systematic review. European Radiology, 32 (10). pp. 7014-7025. ISSN 0938-7994

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Copyright, Publisher and Additional Information: © The Author(s) 2022. 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: Glioma; Magnetic resonance imaging; Reproducibility of results
Dates:
  • Accepted: 10 April 2022
  • Published (online): 29 April 2022
  • Published: October 2022
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)
Funding Information:
FunderGrant number
Cancer Research UK Supplier No: 138573A28832
Depositing User: Symplectic Publications
Date Deposited: 12 May 2022 12:06
Last Modified: 25 Jun 2023 22:58
Status: Published
Publisher: Springer
Identification Number: https://doi.org/10.1007/s00330-022-08807-2
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