Conference item : Abstract
Generalist deep learning for cross-modality landmark annotation in cardiovascular magnetic resonance
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 2.7MB, Terms of use)
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(Preview, Version of record, pdf, 1.7MB, Terms of use)
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- Publisher copy:
- 10.1016/j.jocmr.2025.102264
Authors
- Publisher:
- Elsevier
- Journal:
- Journal of Cardiovascular Magnetic Resonance More from this journal
- Volume:
- 28
- Issue:
- S1
- Article number:
- 102264
- Publication date:
- 2026-01-28
- Acceptance date:
- 2025-10-29
- Event title:
- SCMR 29th Annual Scientific Sessions
- Event location:
- Rio de Janeiro, Brazil
- Event website:
- https://scmr2026.eventscribe.net/index.asp
- Event start date:
- 2026-02-04
- Event end date:
- 2026-02-07
- DOI:
- Language:
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English
- Subtype:
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Abstract
- Pubs id:
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2307682
- Local pid:
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pubs:2307682
- Deposit date:
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2025-11-03
- ARK identifier:
Terms of use
- Copyright holder:
- Gonzales et al
- Copyright date:
- 2026
- Rights statement:
- ©2026 The Authors. This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.
- Notes:
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This paper will be presented at SCMR 29th Annual Scientific Sessions 4-7 Feb 2026, Rio de Janeiro, Brazil
The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
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