Jianping Xu1,2,3, Sultan Zaman Mahmud1,2, Yi Zhang3, Hye-Young Heo1,2
1Johns Hopkins University School of Medicine, Baltimore, United States of America
2F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States of America
3Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
Presenting Author: Xingwang Yong
Synopsis
Motivation:
Goals:
Approach:
Results:
Full abstract & presentation
The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.
Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.
To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.
1. Kim B, Schär M, Park H, Heo H-Y. A deep learning approach for magnetization transfer contrast MR fingerprinting and chemical exchange saturation transfer imaging. Neuroimage 2020;221:117165. doi:10.1016/j.neuroimage.2020.117165 [doi]
2. Perlman O, Farrar CT, Heo HY. MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification. NMR in Biomedicine 2023;36(6):e4710. doi:10.1002/nbm.4710 [doi]
3. Perlman O, Ito H, Herz K, Shono N, Nakashima H, Zaiss M, Chiocca EA, Cohen O, Rosen MS, Farrar CT. Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning. Nature Biomedical Engineering 2022;6(5):648-657. doi:10.1038/s41551-021-00809-7 [doi]
4. Vladimirov N, Cohen O, Heo H-Y, Zaiss M, Farrar CT, Perlman O. Quantitative molecular imaging using deep magnetic resonance fingerprinting. Nature Protocols 2025:1-31.
5. Perlman O, Herz K, Zaiss M, Cohen O, Rosen MS, Farrar CT. CEST MR‐fingerprinting: practical considerations and insights for acquisition schedule design and improved reconstruction. Magnetic Resonance in Medicine 2020;83(2):462-478. doi:10.1002/mrm.27937 [doi]
6. Singh M, Jiang S, Li Y, Van Zijl P, Zhou J, Heo HY. Bloch simulator–driven deep recurrent neural network for magnetization transfer contrast MR fingerprinting and CEST imaging. Magnetic Resonance in Medicine 2023;90(4):1518-1536. doi:10.1002/mrm.29748 [doi]
7. Raissi M, Perdikaris P, Karniadakis GE. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. Journal of Computational physics 2019;378:686-707. doi:10.1016/j.jcp.2018.10.045 [doi]
8. Kim M, Gillen J, Landman BA, Zhou J, Van Zijl PC. Water saturation shift referencing (WASSR) for chemical exchange saturation transfer (CEST) experiments. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine 2009;61(6):1441-1450. doi:10.1002/mrm.22076 [doi]
9. Hartigan JA, Wong MA. Algorithm AS 136: A k-means clustering algorithm. Journal of the Royal Statistical Society Series C (applied statistics) 1979;28(1):100-108. doi:10.2307/2346830 [doi]
10. Heo HY, Zhang Y, Lee DH, Hong X, Zhou J. Quantitative assessment of amide proton transfer (APT) and nuclear Heo HY, Zhang Y, Jiang S, Lee DH, Zhou J. Quantitative assessment of amide proton transfer (APT) and nuclear overhauser enhancement (NOE) imaging with extrapolated semisolid magnetization transfer reference (EMR) signals: II. Comparison of three EMR models and application to human brain glioma at 3 Tesla. Magnetic Resonance in Medicine 2016;75(4):1630-1639. doi:10.1002/mrm.25795 [doi]