Accelerated High-resolution T1- and T2-weighted Breast MRI with Deep Learning Super-resolution Reconstruction
DL for denoising and resolution upscaling reduces acquisition time and improves image quality for T1w and T2w breast MRI.
Authors
- Daniel Kuetting (ORCID: https://orcid.org/0000-0001-6520-1020)
- Julian Alexander Luetkens (ORCID: https://orcid.org/0000-0002-7715-4636)
- Tatjana Dell (ORCID: https://orcid.org/0000-0002-2835-8560)
- Claus C. Pieper (ORCID: https://orcid.org/0000-0002-0893-1200)
- Johannes Peeters (ORCID: https://orcid.org/0000-0001-6639-0863)
- Narine Mesropyan (ORCID: https://orcid.org/0000-0002-5871-3965)
- Alexandra Sommer
- C Leutner
- Alexander Isaak (ORCID: https://orcid.org/0000-0003-2016-6166)
- Leon Bischoff (ORCID: https://orcid.org/0000-0001-5193-5226)
- Christoph Katemann
- O. Weber (ORCID: https://orcid.org/0000-0002-2569-0875)
- Asadeh Lakghomi
Institutions
- University Hospital Bonn (DE)
- Philips (Netherlands) (NL)
- Philips (Germany) (DE)
Publication Details
- Journal
- Academic Radiology
- Published
- 2025-01-09
- DOI
- https://doi.org/10.1016/j.acra.2024.12.055
- Citations
- 8
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 10.88