Referenceless 4D flow cardiovascular magnetic resonance with deep learning
Deep learning-enabled referenceless 4D flow CMR permits velocities and flow volumes quantification comparable to conventional 4D flow. Omitting the reference encoding reduces the amount of acquired data by 25%, thus allowing shorter scan times or improved resolution, which is valuable for utilization in the clinical routine.
Authors
- Chiara Trenti (ORCID: https://orcid.org/0000-0002-0770-0769)
- Carl‐Johan Carlhäll (ORCID: https://orcid.org/0000-0003-2198-9690)
- Petter Dyverfeldt (ORCID: https://orcid.org/0000-0002-3051-661X)
- Tino Ebbers (ORCID: https://orcid.org/0000-0003-1395-8296)
- Jan Engvall (ORCID: https://orcid.org/0000-0002-5716-5098)
- Erik Ylipää
Institutions
- Linköping University (SE)
Publication Details
- Journal
- Journal of Cardiovascular Magnetic Resonance
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.jocmr.2025.101920
- Citations
- 2
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.72
Funders
- Linköpings Universitet