| 摘要 |
We present a method for informed optimization of sampling vectors in multi-directional diffusion-weighted magnetic resonance imaging. The advantage of this optimization is that it is informed rather than being a naïve optimization of sampling vectors. Typically, sampling vectors are set relatively uniformly along a spherical surface. In this case, a scan at high imaging resolutions utilizes sampling vectors that are chosen based on the knowledge of the overall orientation distribution for the entire sample or region of interest. This overall orientation distribution is obtained by performing multi-directional diffusion-weighted scans at high angular resolution, but low or minimal voxel resolution. A subset of the vectors used in this high-angular-resolution scan is chosen to minimize the error in the final results. This optimal subset is not necessarily uniform in space.
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