Assessing the reproducibility of a subject-specific finite element modelling pipeline for the human metastatic vertebrae.

Roger, R., Ghosh, R. orcid.org/0000-0002-1185-2060, Cai, Y. et al. (5 more authors) (2026) Assessing the reproducibility of a subject-specific finite element modelling pipeline for the human metastatic vertebrae. Scientific Reports. ISSN: 2045-2322

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Item Type: Article
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© The Author(s) 2026. Open Access 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: Computed tomography; Finite element modelling; Image segmentation; Metastatic vertebrae; Reproducibility; Subject-specific
Dates:
  • Submitted: 21 January 2026
  • Accepted: 27 March 2026
  • Published (online): 7 April 2026
  • Published: 7 April 2026
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Mechanical, Aerospace and Civil Engineering
The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health
Date Deposited: 09 Apr 2026 08:24
Last Modified: 09 Apr 2026 08:24
Status: Published online
Publisher: Springer Nature
Refereed: Yes
Identification Number: 10.1038/s41598-026-46900-4
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