<scp>FlowVN</scp> Trained on a Single Dataset Enables Rapid Reconstruction of Highly Accelerated <scp>4D</scp> Flow <scp>MRI</scp> Across Multiple Sites
FlowVN accurately reconstructs highly undersampled 4D Flow MRI from multiple sites using a model trained on a single dataset, maintaining excellent quantitative image quality even at very high acceleration factors.
Authors
- Federica Viola (ORCID: https://orcid.org/0000-0002-0354-7680)
- Chiara Trenti (ORCID: https://orcid.org/0000-0002-0770-0769)
- Petter Dyverfeldt (ORCID: https://orcid.org/0000-0002-3051-661X)
- Tino Ebbers (ORCID: https://orcid.org/0000-0003-1395-8296)
- Tamara Bianchessi (ORCID: https://orcid.org/0000-0001-9709-803X)
- Sohaib A. Qazi (ORCID: https://orcid.org/0000-0003-3869-3482)
- Erik Ylipää
Institutions
- Linköping University (SE)
- Science for Life Laboratory (SE)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2026-02-26
- DOI
- https://doi.org/10.1002/mrm.70317
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00