In this study, we present and validate the efficacy of using a state-of-the-art deep-learning method to achieve submillimeter high-resolution diffusion-weighted (DW) images. The 2D-based deep-learning method was validated by comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) of the deep-learning high-resolution images and the ground-truth.
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