Cagni, Elisabetta, Botti, Andrea, Orlandi, Matteo, Galaverni, Marco, Lotti, Cinzia, Iori, Mauro, Lewis, Geraint and Spezi, Emiliano ![]() ![]() |
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Official URL: https://doi.org/10.3390/app12199493
Abstract
This paper presents a deformable image registration-based method for the quality assurance of head and neck adaptive radiotherapy using digitally post-processed anthropomorphic phantom image datasets. One of the main findings of this work is that spatial and dose errors are a function of the magnitude of the deformation and of the gradient of the dose distribution. This emphasizes the importance of performing patient-specific deformable image registration verification and, consequently, the need to develop and make available tools that are for this purpose.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Publisher: | MDPI |
ISSN: | 2076-3417 |
Date of First Compliant Deposit: | 10 October 2022 |
Date of Acceptance: | 15 September 2022 |
Last Modified: | 09 May 2023 11:32 |
URI: | https://orca.cardiff.ac.uk/id/eprint/153140 |
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