Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
360-04-006 ISMRM Abstract

Complex-Valued MR Fingerprinting (CV-MRF) for Simultaneous Estimation of R2*, Field Perturbations, and Transceive Phase

Accepted
Matthew T Cherukara1,2, Kevin McNally1, Karin Shmueli1, Patrick S Fuchs 1,3
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
2School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
3imec-Vision lab, University of Antwerp, Antwerp, Belgium
Presenting Author: Patrick S Fuchs

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.

Log in

References

1. Shmueli K. Quantitative Susceptibility Mapping. In: Quantitative Magnetic Resonance Imaging. 1st ed. Elsevier; 2020
2. Katscher U, van den Berg CAT. Electric properties tomography: Biochemical, physical and technical background, evaluation and clinical applications. NMR Biomed. 2017;30(8):e3729. doi:10.1002/nbm.3729 [doi]
3. Kim DH, Choi N, Gho SM, Shin J, Liu C. Simultaneous imaging of in vivo conductivity and susceptibility: Simultaneous Electromagnetic Property Imaging. Magn Reson Med. 2014;71(3):1144-1150. doi:10.1002/mrm.24759 [doi]
4. Ma D, Gulani V, Seiberlich N, et al. Magnetic resonance fingerprinting. Nature. 2013;495(7440):187-192. doi:10.1038/nature11971 [doi]
5. Liu T, Wisnieff C, Lou M, Chen W, Spincemaille P, Wang Y. Nonlinear formulation of the magnetic field to source relationship for robust quantitative susceptibility mapping. Magn Reson Med. 2013;69(2):467-476. doi:10.1002/mrm.24272 [doi]
6. QSM Challenge 2.0 Organization Committee, Bilgic B, Langkammer C, et al. QSM reconstruction challenge 2.0: Design and report of results. Magn Reson Med. 2021;86(3):1241-1255. doi:10.1002/mrm.28754 [doi]
7. Chan KS, Ma Y, Lee H, Huang S, Marques JP, Lee HH. GACELLE: GPU-AcCELerated toolbox for high-throughput multidimensionaL quantitative parameter Estimation. In: Proc. Intl. Soc. Mag. Reson. Med. 33. ; 2025
8. Pei M, Nguyen TD, Thimmappa ND, et al. Algorithm for fast monoexponential fitting based on Auto-Regression on Linear Operations (ARLO) of data. Magn Reson Med. 2015;73(2):843-850. doi:10.1002/mrm.25137 [doi]
9. Langkammer C, Schweser F, Shmueli K, et al. Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge. Magn Reson Med. 2018;79(3):1661-1673. doi:10.1002/mrm.26830 [doi]
10. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process. 2004;13(4):600-612. doi:10.1109/tip.2003.819861 [doi]
11. Bilgic B, Costagli M, Chan KS, et al. Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group. Magn Reson Med. 2024;91(5):1834-1862. doi:10.1002/mrm.30006 [doi]
12. Karsa A, Shmueli K. SEGUE: A Speedy rEgion-Growing Algorithm for Unwrapping Estimated Phase. IEEE Trans Med Imaging. 2019;38(6):1347-1357. doi:10.1109/TMI.2018.2884093 [doi]

Cite this abstract