Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
365-06-015 ISMRM Abstract

Deep learning-based phase correction and denoising improves clinical multi-shot DWI

Primary: Diffusion - Diffusion Reconstruction
Secondary: Body - Liver
365-06-015 · Diffusion MRI Reconstruction Methods · Monday, 11 May, 5:05 PM–6:00 PM · Digital Posters Row F
Keywords: Deep learning reconstruction Diffusion-Weighted Imaging Multi-shot EPI DWI Abdominal MRI
Accepted
Ryan Brunsing 1, Sarah Miller1, Sunny Rishi1, Jessica Chong1, Vipul R Sheth1, Matthew J Middione2, Arnaud Guidon2, Quin Lu3, Xinzeng Wang4, Patricia Lan3
1Department of Radiology, Stanford Medicine, Stanford, United States of America
2MR Clinical Solutions & Research Collaborations, GE HealthCare, San Ramon, United States of America
3MR Clinical Solutions & Research Collaborations, GE HealthCare, Menlo Park, United States of America
4MR Clinical Solutions & Research Collaborations, GE Healthcare, Houston, United States of America
Presenting Author: Ryan Brunsing

Synopsis

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References

1. Chen N, Guidon A, Chang H-C, Song AW. A robust multi-shot scan strategy for highn-resolution diffusion weighted MRI enabled by multiplexed sensitivity-encoding (MUSE). NeuroImage. 2013;72:41–47. doi: 10.1016/j.neuroimage.2013.01.038. [doi]
2. Hosseiny M, Sung KH, Felker E, et al. Read-out Segmented Echo Planar Imaging with Two-Dimensional Navigator Correction (RESOLVE): An Alternative Sequence to Improve Image Quality on Diffusion-Weighted Imaging of Prostate. Br J Radiol. 2022;95(1136):20211165. doi: 10.1259/bjr.20211165. [doi]
3. Lee PK, Zhou X, Hargreaves BA. Robust multishot diffusion-weighted imaging of the abdomen with region-based shot rejection. Magn Reson Med. 2024;92(2):519–531. doi: 10.1002/mrm.30102. [doi]
4. Wang K, Middione MJ, Loening AM, et al. Motion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising. Invest Radiol. 2025; doi: 10.1097/RLI.0000000000001148. [doi]
5. Lan P., Wang X., Guidon G. Reduced Noise and Motion Artifacts for MUSE Reconstruction using Deep Learning-based Phase Correction. ISMRM Annual Meeting. 2024. Singapore. Abstract #2416. https://archive.ismrm.org/2024/2416.html

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/365-06-015