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Abstract #4805

Advancing Multishot EPI Reconstruction for Diffusion MRI: From Locally to Non-Locally Low-Rank Methods

Yiming Dong1, Xinyu Ye2, Chang Li3, Matthias J.P. van Osch1, and Peter Börnert1,4
1C.J. Gorter MRI Center, Department of Radiology, LUMC, Leiden, Netherlands, 2Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 3Division of Image Processing, Department of Radiology, LUMC, Leiden, Netherlands, 4Philips Innovative Technologies Hamburg, Hamburg, Germany

Synopsis

Keywords: Diffusion Reconstruction, Diffusion Reconstruction

Motivation: High-SNR, high-resolution diffusion MRI is essential for detailed anatomical imaging. To this end, multishot EPI (ms-EPI) can be helpful but is challenged by low SNR and motion-induced phase variations.

Goal(s): This study aims to develop a new non-locally low-rank reconstruction (NLLR) method that corrects motion-induced shot-to-shot phase variations and improves noise suppression in DW ms-EPI, improving high-resolution DWI.

Approach: We extend the shot-locally low-rank (LLR) method by incorporating spatially non-local patch similarities into ms-EPI reconstruction that improves low-rank approximations and noise reduction.

Results: NLLR achieved higher structural clarity and higher SNR compared to the LLR method in both simulations and in-vivo validations.

Impact: This study presents a robust non-local-low-rank reconstruction technique for multi-shot EPI in diffusion MRI that achieves superior image quality and SNR. These advances provide clearer anatomical details, supporting improved diagnosis and encouraging the exploration of non-local approaches in high-resolution imaging.

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Keywords