In order to establish a benchmark for future studies, we utilize a data driven approach towards optimizing diffusion sampling for an ultra-high-performance gradient MRI sub-system as a means to establish minimal discrepancy compared to a fully sampled, defined superset. This study focused on b-value contribution and the impact of decreased sampling on uncertainty of diffusion and kurtosis tensor estimates, and fiber orientation to resolve sub-voxel information.
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