Deep learning reconstruction for accelerated high-resolution upper abdominal MRI improves lesion detection without time penalty
HR-VIBE<sub>DL</sub> images of the upper abdomen result in superior image quality, better lesion conspicuity, and improved lesion detection without time penalty by comparsion with conventional VIBE images.
Authors
- Konstantin Nikolaou (ORCID: https://orcid.org/0000-0003-2668-7325)
- Sebastian Gassenmaier (ORCID: https://orcid.org/0000-0003-3701-2227)
- Reza Dehdab (ORCID: https://orcid.org/0000-0002-3496-8808)
- Dominik M. Nickel (ORCID: https://orcid.org/0000-0002-0360-7233)
- Judith Herrmann (ORCID: https://orcid.org/0000-0003-1535-8980)
- Haidara Almansour (ORCID: https://orcid.org/0000-0003-1672-3855)
- Saif Afat (ORCID: https://orcid.org/0000-0002-6861-6245)
- Jan M. Brendel (ORCID: https://orcid.org/0000-0002-2729-610X)
- Johann Jacoby (ORCID: https://orcid.org/0000-0002-7017-9638)
- Sebastian Werner (ORCID: https://orcid.org/0000-0003-4542-6462)
- Stephan Ursprung
Institutions
- STZ eyetrial (DE)
- Siemens Healthcare (United States) (US)
- Siemens Healthineers (Germany) (DE)
- University of Tübingen (DE)
Publication Details
- Journal
- Diagnostic and Interventional Imaging
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1016/j.diii.2024.09.008
- Citations
- 10
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 4.04