Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
461-03-007 ISMRM Abstract

Model-based distortion correction for EPI MR images using learnt priors

Primary: Acquisition & Reconstruction - Artifacts and Correction Strategies
Secondary: Acquisition & Reconstruction - Image Reconstruction: AI
461-03-007 · Artifact Correction Strategies in Brain and Body · Tuesday, 12 May, 1:40 PM–2:35 PM · Digital Posters Row B
Keywords: EPI Distortion correction Model-based reconstruction Artificial Intelligence (AI) Deep Learning Diffusion-weighted imaging (DWI)
Accepted
SUDHANYA Chatterjee1, Florian Wiesinger2, Dattesh Dayanand Shanbhag 1, Patricia Lan3, Rajagopalan Sundaresan1, Marc Lebel4, Arnaud Guidon5
1GE HealthCare, Bangalore, India
2GE Healthcare, Munich, Germany
3GE HealthCare, Menlo Park, United States of America
4GE HealthCare, AB CA, United States of America
5GE HealthCare, San Ramon, United States of America
Presenting Author: Dattesh Dayanand Shanbhag

Synopsis

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References

1. Munger, P., Crelier, G.R., Peters, T.M. and Pike, G.B., 2000. An inverse problem approach to the correction of distortion in EPI images. IEEE Transactions on Medical Imaging, 19(7), pp.681-689. doi:10.1109/42.875186 [doi]
2. Yarach, U., In, M.H., Chatnuntawech, I., Bilgic, B., Godenschweger, F., Mattern, H., Sciarra, A. and Speck, O., 2017. Model‐based iterative reconstruction for single‐shot EPI at 7 T. Magnetic resonance in medicine, 78(6), pp.2250-2264. https://doi.org/10.1002/mrm.26633 [doi]
3. Zaid Alkilani, A., Çukur, T. and Saritas, E.U., 2024. FD‐Net: An unsupervised deep forward‐distortion model for susceptibility artifact correction in EPI. Magnetic Resonance in Medicine, 91(1), pp.280-296. https://doi.org/10.1002/mrm.29851 [doi]
4. Ge, Nuowei, et al., Dynamic distortion correction of ME-EPI using learning-based single-scan multi-echo blip up-down acquisition (ME-BUDA), #2639, ISMRM 2024.
5. Pruessmann, K.P., Weiger, M., Scheidegger, M.B. and Boesiger, P., 1999. SENSE: sensitivity encoding for fast MRI. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 42(5), pp.952-962. https://doi.org/10.1002/(SICI)1522-2594(199911)42:5<952::AID-MRM16>3.0.CO;2-S [doi]
6. Yeung, K., Tobler, C., Schulte, R.F. et al. Algebraic methods and computational strategies for pseudoinverse-based MR image reconstruction (Pinv-Recon). Sci Rep 15, 37997 (2025). https://doi.org/10.1038/s41598-025-21929-z [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/461-03-007