Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
364-01-007 ISMRM Abstract

Activation Spread due to Local Low-Rank Denoising in SMS-EPI Task-Based fMRI Data

Primary: Brain Function and fMRI - fMRI Analysis
Secondary: Analysis Methods - Image Enhancement
364-01-007 · fMRI: Analyses · Monday, 11 May, 8:20 AM–9:15 AM · Digital Posters Row E
Keywords: fMRI (task based) fMRI Analysis Denoising NORDIC Local Low-rank
Accepted
Sofia Kardonik 1, Douglas C Noll2, Jeffrey A Fessler3,4,5
1Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, United States of America
2Biomedical Engineering, University of Michigan, Ann Arbor, United States of America
3Department of Radiology, University of Michigan, Ann Arbor, United States of America
4Department of Biomedical Engineering, University of Michigan, Ann Arbor, United States of America
5Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, United States of America
Presenting Author: Sofia Kardonik

Synopsis

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References

1. Vizioli, L., Moeller, S., Dowdle, L., Akçakaya, M., De Martino, F., Yacoub, E., & Uğurbil, K. (2021). Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging. Nature communications, 12(1), 5181. https://doi.org/10.1038/s41467-021-25431-8 [doi]
2. Veraart, J., Novikov, D. S., Christiaens, D., Ades-Aron, B., Sijbers, J., & Fieremans, E. (2016). Denoising of diffusion MRI using random matrix theory. Neuroimage, 142, 394-406. https://doi.org/10.1016/j.neuroimage.2016.08.016 [doi]
3. Nadakuditi, R. R. (2014). OptShrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage. IEEE Transactions on Information Theory, 60(5), 3002-3018. https://doi.org/10.1109/TIT.2014.2311661 [doi]
4. Setsompop, K., Gagoski, B. A., Polimeni, J. R., Witzel, T., Wedeen, V. J., & Wald, L. L. (2012). Blipped‐controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g‐factor penalty. Magnetic resonance in medicine, 67(5), 1210-1224. https://doi.org/10.1002/mrm.23097 [doi]
5. Lobos, R. A., Chan, C. C., & Haldar, J. P. (2023). New theory and faster computations for subspace-based sensitivity map estimation in multichannel MRI. IEEE transactions on medical imaging, 43(1), 286-296. https://doi.org/10.1109/TMI.2023.3297851 [doi]
6. Dowdle, L. T., Vizioli, L., Moeller, S., Akçakaya, M., Olman, C., Ghose, G., ... & Uğurbil, K. (2023). Evaluating increases in sensitivity from NORDIC for diverse fMRI acquisition strategies. NeuroImage, 270, 119949. https://doi.org/10.1016/j.neuroimage.2023.119949 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/364-01-007