Saturation transfer <scp>MR</scp> fingerprinting for magnetization transfer contrast and <scp>chemical exchange saturation transfer</scp> quantification
This study highlights the feasibility of the deep learning-based ST-MRF imaging for rapid and accurate quantification of free bulk water, magnetization transfer contrast, APT parameters, and B<sub>0</sub> field inhomogeneity.
Authors
- Beomgu Kang (ORCID: https://orcid.org/0000-0002-1919-1850)
- Sultan Z. Mahmud (ORCID: https://orcid.org/0000-0002-0670-0716)
- Peter C.M. van Zijl (ORCID: https://orcid.org/0000-0002-9706-1066)
- Jinyuan Zhou (ORCID: https://orcid.org/0000-0002-6684-7920)
- Hye‐Young Heo (ORCID: https://orcid.org/0000-0002-7297-2015)
- Munendra Singh (ORCID: https://orcid.org/0000-0002-4988-6573)
Institutions
- Kennedy Krieger Institute (US)
- Johns Hopkins University (US)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2025-04-14
- DOI
- https://doi.org/10.1002/mrm.30532
- Citations
- 7
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 9.52
Funders
- National Institutes of Health