Efficacy of compressed sensing and deep learning reconstruction for adult female pelvic MRI at 1.5 T
Patients underwent MRI with T1- and T2-weighted sequences using CS and PI. All CS data was reconstructed with and without DLR. CS with DLR allowed for examination times significantly shorter than those of PI and provided significantly higher signal- and CNRs, as well as OIQ.
Authors
- Masao Yui (ORCID: https://orcid.org/0000-0002-2562-0623)
- Hiroyuki Nagata (ORCID: https://orcid.org/0000-0001-7998-955X)
- Natsuka Yazawa
- Kaori Yamamoto (ORCID: https://orcid.org/0000-0003-0884-3419)
- Yoshiharu Ohno (ORCID: https://orcid.org/0000-0002-4431-1084)
- Masato Ikedo (ORCID: https://orcid.org/0000-0002-2701-1899)
- Ikki Tozawa
- Takahiro Ueda (ORCID: https://orcid.org/0000-0003-2577-3619)
- Yoshiyuki Ozawa (ORCID: https://orcid.org/0000-0002-8252-1947)
- Masahiko Nomura
Institutions
- Canon (Japan) (JP)
- Fujita Health University (JP)
- Fujita Health University Hospital (JP)
- Fujita Health University Bantane Hospital
- Canon Medical Systems Corporation (Japan) (JP)
Publication Details
- Journal
- European Radiology Experimental
- Published
- 2024-09-10
- DOI
- https://doi.org/10.1186/s41747-024-00506-5
- Citations
- 3
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- Canon Medical Systems Corporation