Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
552-02-005 / 552-02-005 ISMRM Abstract

Dynamic, Motion-Triggered B₀ Estimation for Retrospective SAMER Motion Correction in T₂*w SWI and QSM at 3T and 7T

Primary: Acquisition & Reconstruction - Motion Correction: Neuro
Secondary: Acquisition & Reconstruction - Artifacts and Correction Strategies
552-02-005 · Quantitative Imaging: Relaxometry, Multiparametric, MR Fingerprinting, and Synthetic MRI · Wednesday, 13 May, 1:40 PM–3:16 PM · Power Pitch Theatre 2
552-02-005 · Quantitative Imaging: Relaxometry, Multiparametric, MR Fingerprinting, and Synthetic MRI · Wednesday, 13 May, 1:40 PM–3:16 PM · Power Pitch Theatre 2
Keywords: Motion Correction 7T Deep learning reconstruction Navigators B0 susceptibility
Accepted
Daniel M Polak 1, Jeanette C Deck2,3,4, Josef Pfeuffer5, Hongli Fan1, Yimeng Lin6, Daniel Nicolas Splitthoff5, Bryan Clifford1, Jonathan R Polimeni7, Lawrence L Wald8, Kawin Setsompop7, Stephen Cauley1, Nan Wang7
1Siemens Medical Solutions USA, Inc., Malvern, United States of America
2Department of Radiology, Balgrist University Hospital, Zurich, Switzerland
3Faculty of Medicine, University of Zurich, Zurich, Switzerland
4Swiss Innovation Hub, Siemens Healthineers International AG, Switzerland
5Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany
6Electrical Engineering, Stanford University, Stanford, United States of America
7Department of Radiology, Stanford University, Stanford, United States of America
8Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, United States of America
Presenting Author: Daniel M Polak

Synopsis

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References

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2. Y. Brackenier et al., “Data-driven motion-corrected brain MRI incorporating pose-dependent B0 fields,” Magn. Reson. Med., vol. 88, no. 2, pp. 817–831, 2022.
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4. N. Wang, “Scout-based Multi-Echo NAvigating (SMENA) for high temporal resolution motion and B0 estimation: applications to EPTI and multi-echo GRE,” in Proc. Intl. Soc. Mag. Reson. Med. 33, 2025.
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7. M. W. Haskell, S. F. Cauley, and L. L. Wald, “TArgeted Motion Estimation and Reduction (TAMER): Data consistency based motion mitigation for mri using a reduced model joint optimization,” IEEE Trans. Med. Imaging, vol. 37, no. 5, pp. 1253–1265, 2018.
8. J. Cordero-Grande, L., Teixeira, R., Hughes, E., Hutter, J., Price, A., & Hajnal et al., “Sensitivity Encoding for Aligned Multishot Magnetic Resonance Reconstruction,” IEEE Trans. Comput. Imaging, vol. 2, no. 3, pp. 266–280, 2016.
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12. D. Polak et al., “Integrating scout and guidance line-based retrospective motion correction into a 3D deep learning reconstruction for fast and robust brain MRI,” in Proc Intl Soc Mag Reson Med, 2024.
13. S.-M. Gho et al., “Susceptibility map-weighted imaging (SMWI) for neuroimaging,” Magn. Reson. Med., vol. 72, no. 2, pp. 337–346, 2014.
14. J. Pfeuffer, K. Eckstein, and S. Bollmann, “Advances In SWI And QSM,” MAGNETOM FLASH, vol. 87, no. 2/2024, pp. 88–99.
15. A. W. Stewart et al., “QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping,” Magn. Reson. Med., vol. 87, no. 3, pp. 1289–1300, 2022.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/552-02-005