Automatic field-of-view planning for magnetic resonance shoulder imaging using Deep Learning
DL-based automated FOV prescription for shoulder MRI achieves performance comparable to radiographers, generalizes across institutions, and demonstrates high clinical utility.
Authors
- Armin Lühr (ORCID: https://orcid.org/0000-0002-9450-6859)
- Marcel Gratz (ORCID: https://orcid.org/0000-0001-9723-5233)
- Lale Umutlu (ORCID: https://orcid.org/0000-0001-5215-7171)
- Mathias Holtkamp
- Aydin Demircioğlu
- Kai Nassenstein
- Anton Sheahan Quinsten
- Simon Joshua Hornisch
- Jens Kleesiek
- Moon-Sung Kim
- Michael Forsting
Institutions
- Erwin L. Hahn Institute for Magnetic Resonance Imaging (DE)
- TU Dortmund University (DE)
- Essen University Hospital (DE)
Publication Details
- Journal
- Journal of medical imaging and radiation sciences
- Published
- 2026-02-12
- DOI
- https://doi.org/10.1016/j.jmir.2026.102197
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00