DTI normalization using AIR and LDDMM algorithm. Finally,

DTI images were preprocessed using CATNAP (Coregistration, Adjustment,
and Tensor-solving, a Nicely Automated Program; http://iacl.ece.jhu.edu/?bennett/catnap/, JHU School of Medicine, Baltimore,
Maryland, USA) to
correct for motion artifacts and coregister the DTI images to the reference
images (i.e., the mean b = 0 s/mm2 image) using 12-parameter
(affine) registration, which additionally corrects for eddy current distortions.

As well, CATNAP automatically extracts the six tensor images (dxx, dyy, dzz,
dxy, dxz, dyz) (22). Similar to MWF and T1w/T2w
mappings, a two-step skull stripping procedure was applied to the six tensor
images as well as the reference image; followed by a two-step normalization
using AIR and LDDMM algorithm. Finally, the overall Kimap (i.e. affine plus
LDDMM non-linear transformations) was applied to each subject’s tensor images.

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The normalized subject tensor images were then used to generate normalized
fractional anisotropy (FA) and mean diffusivity (MD) maps using the DTIStudio
Toolbox (63) within MRI studio.