Accelerated deep learning-based function assessment in cardiovascular magnetic resonance
DL cine allows fast and accurate quantification of LV and RV parameters and comparable image quality with conventional bSSFP.
Authors
- Luca Pugliese (ORCID: https://orcid.org/0000-0001-9061-7247)
- Tiziano Polidori (ORCID: https://orcid.org/0000-0002-4633-6760)
- Andrea Laghi (ORCID: https://orcid.org/0000-0002-3091-7819)
- Giuseppe Tremamunno (ORCID: https://orcid.org/0000-0001-6484-9765)
- Giovanna Grazia Bona
- Domenico De Santis (ORCID: https://orcid.org/0000-0002-1197-456X)
- Michela Polici (ORCID: https://orcid.org/0000-0001-7331-6901)
- Antonella Del Gaudio (ORCID: https://orcid.org/0000-0001-6017-8976)
- Damiano Caruso (ORCID: https://orcid.org/0000-0001-9285-4764)
- Marta Zerunian (ORCID: https://orcid.org/0000-0003-4635-7999)
- Curzio Santangeli (ORCID: https://orcid.org/0009-0004-4364-783X)
- Federica Fanelli
Institutions
- Azienda Ospedaliera Sant'Andrea (IT)
Publication Details
- Journal
- La radiologia medica
- Published
- 2025-05-17
- DOI
- https://doi.org/10.1007/s11547-025-02019-6
- Citations
- 2
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.72