From Faster Frames to Flawless Focus: Deep Learning HASTE in Postoperative Single Sequence MRI
HASTE-DL offers superior image quality, improved visualization of critical structures, such as drainages, vessels, bile and pancreatic ducts, and reduced acquisition time, making it an effective alternative to the standard HASTE sequence, and a promising complementary tool in the postoperative imaging workflow.
Authors
- Thomas Malinka (ORCID: https://orcid.org/0000-0002-5860-5710)
- Dominik Geisel (ORCID: https://orcid.org/0000-0001-7348-0971)
- Johannes Kolck (ORCID: https://orcid.org/0000-0001-9843-2247)
- Clarissa Hosse (ORCID: https://orcid.org/0000-0002-4383-5716)
- Thula Walter (ORCID: https://orcid.org/0000-0002-2003-8351)
- Bernhard Gebauer (ORCID: https://orcid.org/0000-0002-9948-7220)
- Uli Fehrenbach (ORCID: https://orcid.org/0000-0003-3622-3268)
- Moritz Wagner (ORCID: https://orcid.org/0000-0002-5078-0725)
- Fabio Pivetta (ORCID: https://orcid.org/0000-0002-1867-2900)
Institutions
- Charité - Universitätsmedizin Berlin (DE)
Publication Details
- Journal
- Academic Radiology
- Published
- 2025-06-24
- DOI
- https://doi.org/10.1016/j.acra.2025.05.039
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00