Model-based deep learning with fully connected neural networks for accelerated magnetic resonance parameter mapping
The proposed model had significantly smaller reconstruction errors than the conventional models. The proposed method can be applied to other qMRI sequences and has the flexibility to replace the image reconstruction module to improve performance.
Authors
- Yasuhiko Terada (ORCID: https://orcid.org/0000-0002-8583-3057)
- Toru Shirai (ORCID: https://orcid.org/0000-0001-6355-9037)
- Naoto Fujita (ORCID: https://orcid.org/0000-0001-9416-3502)
- Suguru Yokosawa
Institutions
- University of Tsukuba (JP)
- Fujifilm (Japan) (JP)
Publication Details
- Journal
- International Journal of Computer Assisted Radiology and Surgery
- Published
- 2025-05-03
- DOI
- https://doi.org/10.1007/s11548-025-03356-7
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Japan Society for the Promotion of Science