A benchmark challenge shows that voxel-wise MLP harmonization, RISH mapping, and NeSH resampling reduce cross-protocol bias in tractometry and connectomics, with the MLP requiring paired same-subject data.
pnlbwh/dmriharmonization: Multi-site dmri harmonization
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MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI
A benchmark challenge shows that voxel-wise MLP harmonization, RISH mapping, and NeSH resampling reduce cross-protocol bias in tractometry and connectomics, with the MLP requiring paired same-subject data.