Open-Source Pre-Clinical Image Segmentation: Mouse cardiac MRI datasets with a deep learning segmentation framework
This work provides the first open-access mouse cardiac MRI dataset, an open-source DL segmentation model, and an accessible inference platform. These tools establish a benchmark for pre-clinical cardiac MRI, enabling reproducible, scalable, and community-driven development of DL methods to accelerate cardiovascular research.
Authors
- R Campbell (ORCID: https://orcid.org/0000-0002-7457-9065)
- Daniel J. Stuckey (ORCID: https://orcid.org/0000-0001-8888-627X)
- Jennifer Anne Steeden (ORCID: https://orcid.org/0000-0002-9792-2022)
- Mark C. Wrobel
- Muthurangu Vivek
- Zhiping Feng
- Wan Shah
- Emily Deniszczyc
- Stephanie Anderson
- Tina Yao
Institutions
- Queen Mary University of London (GB)
- Cardiovascular Institute of the South (US)
- University of Oxford (GB)
- University College London (GB)
Publication Details
- Journal
- Journal of Cardiovascular Magnetic Resonance
- Published
- 2026-02-01
- DOI
- https://doi.org/10.1016/j.jocmr.2026.102706
- Primary Topic
- Medical Image Segmentation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00