Deformable image registration based on single or multi-atlas methods for automatic muscle segmentation and the generation of augmented imaging datasets

Henson, W.H. orcid.org/0000-0002-5001-772X, Mazzá, C. and Dall’Ara, E. (2023) Deformable image registration based on single or multi-atlas methods for automatic muscle segmentation and the generation of augmented imaging datasets. PLOS ONE, 18 (3). e0273446.

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2023 Henson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. https://creativecommons.org/licenses/by/4.0/
Keywords: Magnetic resonance imaging; Body limbs; Imaging techniques; Muscle tissue; Adipose tissue; Fats; Deep learning; Skeletal muscles
Dates:
  • Accepted: 15 February 2023
  • Published (online): 10 March 2023
  • Published: 10 March 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 16 Mar 2023 14:54
Last Modified: 16 Mar 2023 14:54
Status: Published
Publisher: Public Library of Science (PLoS)
Refereed: Yes
Identification Number: https://doi.org/10.1371/journal.pone.0273446

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