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Abstract #0981

Fat-shift suppression in diffusion MRI using rotating phase encoding and localised outlier weighting

Daan Christiaens1,2, Lucilio Cordero-Grande1,3, Jana Hutter3,4, Anthony N Price3,4, Jonathan O'Muircheartaigh1, Katy Vecchiato1, Joseph V Hajnal1,3, and J-Donald Tournier1,3
1Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2Department of Electrical Engineering (ESAT/PSI), KU Leuven, Leuven, Belgium, 3Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 4Centre for the Developing Brain, King's College London, London, United Kingdom

Diffusion MRI is prone to fat-shift artefacts, especially in accelerated diffusion MRI with higher b-values. Building on the property that the fat signal localisation depends on the phase encoding direction, we propose to suppress fat-shift artefacts in post-processing using localised outlier rejection across 4 different phase encoding directions. To this end, we extend a retrospective diffusion MRI motion correction framework with local outlier weights, defined as a voxel-wise measure of the MR reconstruction residuals. Comparative results in a pediatric brain imaging cohort show that the proposed method reduces fat-shift artefacts in the parenchyma without affecting the reconstruction in uncorrupted regions.

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