Precision, prognosis, and clinical performance of rounded and trabecular segmentation of cine cardiovascular magnetic resonance
We developed an automated method for annotating papillary muscles and trabeculae from cardiac MR images with low error rates. We found higher precision than clinicians in ejection fraction. There was similar precision and prognostication to an ML rounded model with similarly low error rates. Findings support the feasibility of automated trabecular segmentation in clinical care and clinical trials.
Authors
- James Moon (ORCID: https://orcid.org/0000-0001-8071-1491)
- Iain Pierce (ORCID: https://orcid.org/0000-0001-8546-5023)
- Karan Punjabi (ORCID: https://orcid.org/0000-0003-0361-0640)
- Peter Kellman (ORCID: https://orcid.org/0000-0002-9875-6070)
- Hunain Shiwani (ORCID: https://orcid.org/0000-0002-0046-2884)
- Anish Bhuva (ORCID: https://orcid.org/0000-0001-7532-7815)
- Thomas A. Treibel (ORCID: https://orcid.org/0000-0003-1560-7414)
- Charlotte Manisty (ORCID: https://orcid.org/0000-0003-0245-7090)
- George Joy (ORCID: https://orcid.org/0000-0003-1467-5490)
- Hui Xue (ORCID: https://orcid.org/0000-0002-4561-5530)
- Dhruv Thakur
- Rhodri Davies (ORCID: https://orcid.org/0000-0001-7630-7517)
- Mohammed Alzahir
- Jessica Artico (ORCID: https://orcid.org/0000-0001-7112-4607)
- Erik B. Schelbert (ORCID: https://orcid.org/0000-0003-0356-4437)
Institutions
- Microsoft (United States) (US)
- National Institutes of Health (US)
- St Bartholomew's Hospital (GB)
- Allina Health (US)
- United Hospital (US)
- Futures Group (United States) (US)
- National Heart, Lung, and Blood Institute (US)
- University College London (GB)
Publication Details
- Journal
- Journal of Cardiovascular Magnetic Resonance
- Published
- 2025-11-25
- DOI
- https://doi.org/10.1016/j.jocmr.2025.102014
- Primary Topic
- Medical Image Segmentation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00