Quantitative maps obtained from Diffusion Tensor are very useful for investigating microstructural changes that occur in brain diseases. However, the long acquisition times required for a fully sampled diffusion-weighted space makes their clinical use unfeasible. Here we have adapted a U-net that obtains reliable Fractional Anisotropy (FA) maps from a reduced set of 10 Diffusion Weighted volumes (that can be acquired in less than 1 min). Our network was applied to two independent, clinical datasets, without retraining, and produced FA that retained clinical sensitivity and characteristic FA value distributions in the brain white matter.
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