Super-resolution deep learning reconstruction to evaluate lumbar spinal stenosis status on magnetic resonance myelography
SR-DLR improved the image quality of lumbar MR myelographs compared to DLR and ZIP, and was associated with better interobserver agreement during assessment of lumbar spinal stenosis status.
Authors
- Hiroyuki Akai (ORCID: https://orcid.org/0000-0002-6494-1091)
- Yuichi Morita (ORCID: https://orcid.org/0000-0002-7329-7496)
- Masaaki Akahane (ORCID: https://orcid.org/0000-0003-4355-0187)
- Yusuke Asari
- Mariko Kurokawa (ORCID: https://orcid.org/0000-0002-3907-9188)
- Shigeru Kiryu (ORCID: https://orcid.org/0000-0003-1440-9483)
- Koichiro Yasaka (ORCID: https://orcid.org/0000-0002-0324-6562)
- Osamu Abe
- Taku Tajima
- Kuni Ohtomo
- Naoki Yoshioka
Institutions
- Systems Biology Institute (JP)
- Mita Hospital (JP)
- The University of Tokyo (JP)
- International University of Health and Welfare (JP)
Publication Details
- Journal
- Japanese Journal of Radiology
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1007/s11604-025-01787-5
- Citations
- 2
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- Canon Medical Systems Corporation