Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
569-02-014 ISMRM Abstract

One-shot Prediction of Pose-Dependent B₀ Field Variations

Primary: Physics & Engineering - Bioeffects & Magnetic Fields
Secondary: Acquisition & Reconstruction - Artifacts and Correction Strategies
569-02-014 · Novel Pulse Sequences and Reconstruction Strategies · Wednesday, 13 May, 9:15 AM–10:10 AM · Digital Posters Row J
Keywords: Motion B0 Inhomogeneity Physics-informed Deep Learning Field mapping OFF-RESONANCE
Accepted
Fatemeh Ebrahiminia 1,2, Mark Chiew1,2
1Department of Medical Biophysics, University of Toronto, Toronto, Canada
2Physical Science Platform, Sunnybrook Research Institute, Toronto, Canada
Presenting Author: Fatemeh Ebrahiminia

Synopsis

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References

1. Van Gelderen, P., De Zwart, J. A., Starewicz, P., Hinks, R. S. & Duyn, J. H. Real‐time shimming to compensate for respiration‐induced B0 fluctuations. Magnetic Resonance in Med 57, 362–368 (2007). https://doi.org/10.1002/mrm.21136 [doi]
2. Zaitsev, M., Maclaren, J. & Herbst, M. Motion artifacts in MRI: A complex problem with many partial solutions. Magnetic Resonance Imaging 42, 887–901 (2015). https://doi.org/10.1002/jmri.24850 [doi]
3. Brackenier, Y. et al. Data‐driven motion‐corrected brain MRI incorporating pose‐dependent B0 fields. Magnetic Resonance in Med 88, 817–831 (2022). https://doi.org/10.1002/mrm.29255 [doi]
4. Liu, J., De Zwart, J. A., Van Gelderen, P., Murphy‐Boesch, J. & Duyn, J. H. Effect of head motion on MRI B0 field distribution. Magnetic Resonance in Med 80, 2538–2548 (2018). https://doi.org/10.1002/mrm.27339 [doi]
5. Motyka, S. et al. Predicting dynamic, motion‐related changes in B0 field in the brain at a 7T MRI using a subject‐specific fine‐trained U‐net. Magnetic Resonance in Med 91, 2044–2056 (2024). https://doi.org/10.1002/mrm.29980 [doi]
6. Marques, J. P. & Bowtell, R. Application of a Fourier-based method for rapid calculation of field inhomogeneity due to spatial variation of magnetic susceptibility. Concepts Magn. Reson. 25B, 65–78 (2005). https://doi.org/10.1002/cmr.b.20034 [doi]
7. Iacono, M. I. et al. MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck. PLoS ONE 10, e0124126 (2015). https://doi.org/10.1371/journal.pone.0124126 [doi]
8. Hatamizadeh, A. et al. UNETR: Transformers for 3D Medical Image Segmentation. Preprint at https://doi.org/10.48550/arXiv.2103.10504 (2021). https://doi.org/10.1109/WACV51458.2022.00181 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/569-02-014