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. 2022 Aug 11;14:923673. doi: 10.3389/fnagi.2022.923673

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Copyright © 2022 Liu, Zhu, Sun, Zhang, Feng, Gjerswold-Selleck, Sikka, Zhu, Liu, Nuriel, Wei, Wu, Vaughan, Laine, Provenzano, Small and Guo.

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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Training strategies of the various DeepContrast models implemented. (A) This training strategy applied to the Healthy Mouse Model. Preprocessing includes intensity normalization and brain extraction. Ground truth Gd-Uptake was derived using the standardized delta-R2 equation. Note that there is an additional standardization step that maps the dynamic range of the standardized delta-R2 to the range of [0, 1], before the application of the brain mask. The loss function was calculated between the Gd-Uptake and the predicted version only using the voxels within the brain mask region. (B) This training strategy applied to the Healthy Human Model. Preprocessing included intensity normalization and brain extraction. Ground truth Gd-Uptake was derived using the steady-state delta-R1 equation. The loss function was calculated between the Gd-Uptake and the predicted version only using the voxels within the brain mask region.