Flow-QSM: bridging learned priors and physical models for quantitative susceptibility mapping
Flow-QSM provides a unified probabilistic framework that
integrates learned generative priors with physics-based constraints for susceptibility
mapping. The proposed approach offers a flexible and principled strategy for addressing
ill-posed inverse problems in computational imaging.
Authors
- Yutao Chen (ORCID: https://orcid.org/0000-0001-9442-6368)
- Haoming Qin
- Lijun Bao
Institutions
- Xiamen University (CN)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- Physics in Medicine and Biology
- Published
- 2026-03-17
- DOI
- https://doi.org/10.1088/1361-6560/ae5388
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00