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. 2023 Sep 11;3:1238566. doi: 10.3389/fradi.2023.1238566

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© 2023 Tang, Chen, D'Souza, Liu, Calamante, Barnett, Cai, Wang and Cabezas.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Detailed framework of the proposed HADTI-Net. HADTI-Net takes a concatenated patch of 3D T1-weighted, b0, and diffusion-weighted images with 6 minimal evenly distributed directions to predict an enhanced LAR-DTI.