Improving hybrid image and structure-based deformable image registration for large internal deformations

Lorenzo Polo, A., Nix, M. orcid.org/0000-0001-7228-7344, Thompson, C. et al. (6 more authors) (2024) Improving hybrid image and structure-based deformable image registration for large internal deformations. Physics in Medicine & Biology, 69 (9). 095011. ISSN 0031-9155

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Item Type: Article
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This item is protected by copyright. This Accepted Manuscript is available for reuse under a CC BY-NC-ND licence. This is an author produced version of an item published in Physics in Medicine & Biology. Uploaded in accordance with the publisher's self-archiving policy.

Keywords: Pelvis; Humans; Tomography, X-Ray Computed; Radiotherapy Planning, Computer-Assisted; Algorithms; Image Processing, Computer-Assisted; Urinary Bladder
Dates:
  • Published: 7 May 2024
  • Published (online): 17 April 2024
  • Accepted: 22 March 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Medical Research (LIMR) > Division of Oncology
Funding Information:
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Grant number
Cancer Research UK Supplier No: 138573
A28832
Depositing User: Symplectic Publications
Date Deposited: 18 Jun 2024 13:26
Last Modified: 18 Jun 2024 13:26
Published Version: https://iopscience.iop.org/article/10.1088/1361-65...
Status: Published
Publisher: IOP Publishing
Identification Number: 10.1088/1361-6560/ad3723
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