Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
560-01-002 ISMRM Abstract

Motion-Aware Fieldmap Estimation for Susceptibility Distortion Correction in EPI

Accepted
Laurin Mordhorst 1,2, Lars Ruthotto3, Siawoosh Mohammadi1,2,4
1Department of Neuroradiology, University of Luebeck, Luebeck, Germany
2Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
3Department of Mathematics and Computer Science, Emory University, Atlanta, United States of America
4Max Planck Research Group MR Physics, Max Planck Institute for Human Development, Berlin, Germany
Presenting Author: Laurin Mordhorst

Synopsis

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References

1. M. Jenkinson, C. F. Beckmann, T. E. J. Behrens, M. W. Woolrich, and S. M. Smith, “FSL,” NeuroImage, vol. 62, no. 2, pp. 782–790, Aug. 2012, doi: 10.1016/j.neuroimage.2011.09.015. [doi]
2. G. David et al., “ACID: A comprehensive toolbox for image processing and modeling of brain, spinal cord, and ex vivo diffusion MRI data,” Imaging Neurosci., vol. 2, pp. 1–34, Sept. 2024, doi: 10.1162/imag_a_00288. [doi]
3. L. Ruthotto, S. Mohammadi, C. Heck, J. Modersitzki, and N. Weiskopf, “Hyperelastic Susceptibility Artifact Correction of DTI in SPM: Workshop on Bildverarbeitung fur die Medizin 2013,” Bildverarb. Für Med. 2013, pp. 344–349, Feb. 2013, doi: 10.1007/978-3-642-36480-8_60. [doi]
4. J. L. R. Andersson, S. Skare, and J. Ashburner, “How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging,” NeuroImage, vol. 20, no. 2, pp. 870–888, Oct. 2003, doi: 10.1016/S1053-8119(03)00336-7. [doi]
5. S. Mohammadi, H. E. Möller, H. Kugel, D. K. Müller, and M. Deppe, “Correcting eddy current and motion effects by affine whole-brain registrations: Evaluation of three-dimensional distortions and comparison with slicewise correction,” Magn. Reson. Med., vol. 64, no. 4, pp. 1047–1056, 2010, doi: 10.1002/mrm.22501. [doi]
6. J. L. R. Andersson and S. N. Sotiropoulos, “An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging,” NeuroImage, vol. 125, pp. 1063–1078, Jan. 2016, doi: 10.1016/j.neuroimage.2015.10.019. [doi]
7. J. L. R. Andersson, M. S. Graham, E. Zsoldos, and S. N. Sotiropoulos, “Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images,” NeuroImage, vol. 141, pp. 556–572, Nov. 2016, doi: 10.1016/j.neuroimage.2016.06.058. [doi]
8. Y. N. Grigoryev, V. A. Vshivkov, and M. P. Fedoruk, Numerical “Particle-in-Cell” Methods: Theory and Applications. De Gruyter, 2012. doi: 10.1515/9783110916706. [doi]
9. L. Ruthotto, S. Mohammadi, and N. Weiskopf, “A new method for joint susceptibility artefact correction and super-resolution for dMRI,” in Medical Imaging 2014: Image Processing, SPIE, Mar. 2014, pp. 170–173. doi: 10.1117/12.2043591. [doi]
10. D. P. Kingma and J. Ba, “Adam: A Method for Stochastic Optimization,” Jan. 30, 2017, arXiv: arXiv:1412.6980. doi: 10.48550/arXiv.1412.6980. [doi]
11. R. Frostig, M. J. Johnson, and C. Leary, “Compiling machine learning programs via high-level tracing,” 2018.
12. B. B. Avants, N. J. Tustison, G. Song, P. A. Cook, A. Klein, and J. C. Gee, “A Reproducible Evaluation of ANTs Similarity Metric Performance in Brain Image Registration,” NeuroImage, vol. 54, no. 3, p. 2033, Sept. 2010, doi: 10.1016/j.neuroimage.2010.09.025. [doi]
13. M. O. Irfanoglu, P. Modi, A. Nayak, E. B. Hutchinson, J. Sarlls, and C. Pierpaoli, “DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) method for correcting echo planar imaging distortions,” NeuroImage, vol. 106, pp. 284–299, Feb. 2015, doi: 10.1016/j.neuroimage.2014.11.042. [doi]
14. X. Cao et al., “MOCO-BUDA: motion-corrected blip-up/down acquisition with joint reconstruction for motion-robust and distortion-free diffusion MRI of the brain,” in Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Virtual Conference, 2020.
15. I. Ellerbrock and S. Mohammadi, “Four in vivo g-ratio-weighted imaging methods: Comparability and repeatability at the group level,” Hum. Brain Mapp., vol. 39, no. 1, pp. 24–41, 2018, doi: 10.1002/hbm.23858. [doi]

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