Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
365-06-001 ISMRM Abstract

Energy-based Profile Encoding for 3D Multi-slab Diffusion-weighted imaging (EPEN)

Primary: Diffusion - Diffusion Reconstruction
Secondary: Acquisition & Reconstruction - Subsampling: Parallel imaging, compressed sensing and low-rank modeling
365-06-001 · Diffusion MRI Reconstruction Methods · Monday, 11 May, 5:05 PM–6:00 PM · Digital Posters Row F
Keywords: Boundary Artifact Correction Multi-Scale Energy Model 3D Multislab Diffusion MRI
Accepted
Reza Ghorbani1, Jyothi Rikhab Chand1, Chu-Yu Lee 2, Mathews Jacob1, Merry Mani3
1Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, United States of America
2Department of Radiology, University of Iowa, Iowa City, United States of America
3Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, United States of America
Presenting Author: Chu-Yu Lee

Synopsis

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References

1. M. Engström and S. Skare, “Diffusion-weighted 3D multislab echo planar imaging for high signal-to-noise ratio efficiency and isotropic image resolution,” Magnetic Resonance in Medicine, vol. 70, no. 6, pp. 1507–1514, Jan. 2013, doi: https://doi.org/10.1002/mrm.24594. [doi]
2. A. T. Van, M. Aksoy, S. J. Holdsworth, D. Kopeinigg, S. B. Vos, and R. Bammer, “Slab profile encoding (PEN) for minimizing slab boundary artifact in three-dimensional diffusion-weighted multislab acquisition,” Magnetic Resonance in Medicine, vol. 73, no. 2, pp. 605–613, Apr. 2014, doi: https://doi.org/10.1002/mrm.25169. [doi]
3. W. Wu, P. J. Koopmans, R. Frost, and K. L. Miller, “Reducing slab boundary artifacts in three‐dimensional multislab diffusion MRI using nonlinear inversion for slab profile encoding (NPEN),” Magnetic Resonance in Medicine, vol. 76, no. 4, pp. 1183–1195, Oct. 2016, doi: https://doi.org/10.1002/mrm.26027. [doi]
4. K. P. Pruessmann, M. Weiger, P. Börnert, and P. Boesiger, “Advances in sensitivity encoding with arbitrary k-space trajectories,” Magnetic Resonance in Medicine, vol. 46, no. 4, pp. 638–651, Oct. 2001, doi: https://doi.org/10.1002/mrm.1241. [doi]
5. J. R. Chand and M. Jacob, “Multi-Scale Energy (MuSE) Framework for Inverse Problems in Imaging,” IEEE Transactions on Computational Imaging, vol. 10, pp. 1250–1265, Jan. 2024, doi: https://doi.org/10.1109/tci.2024.3449101. [doi]
6. P. Vincent, “A Connection Between Score Matching and Denoising Autoencoders,” Neural Computation, vol. 23, no. 7, pp. 1661–1674, Jul. 2011, doi: https://doi.org/10.1162/neco_a_00142. [doi]
7. C.-Y. Lee and M. Mani, “2D CAIPI accelerated 3D multi-slab diffusion weighted EPI combined with qModeL reconstruction for fast high resolution microstructure imaging,” Magnetic Resonance Imaging, vol. 111, pp. 57–66, Sep. 2024, doi: https://doi.org/10.1016/j.mri.2024.04.003. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/365-06-001