Groupwise regional analysis

perform_dti_regional.py [-h]
                               [--input_dir input_dir | --input_img input_img [input_img ...]]
                               [--rigid_it number] [--affine_it number]
                               [--nonrigid_it number]
                               [--in_atlas_template_fa file]
                               [--in_atlas_template_labels file] -o output_dir
                               [-g]

This workflow takes multiple diffusion tensor images as input. It performs a
groupwise registration using the DTI-TK toolkit (http://dti-
tk.sourceforge.net) The JHU atlas Fractional Anisotropy (FA) image of the
atlas (or the atlas image provided) is then registered to the groupwise FA and
the atlas labels are propagated in the groupwise space The pipeline exports
diffusion based biomarkers (i.e. FA, MD, RD, AD) mean and standard deviations
for each region and each subject present as input

optional arguments:
  -h, --help            show this help message and exit
  --input_dir input_dir
                        Input directory containing the Nifti file(s) to
                        include in the processing
  --input_img input_img [input_img ...]
                        List of Nifti file(s) to include in the processing
  --rigid_it number     Number of iteration to perform for the rigid step
                        (default is 3)
  --affine_it number    Number of iteration to perform for the affine step
                        (default is 3)
  --nonrigid_it number  Number of iteration to perform for the nonrigid step
                        (default is 6)
  --in_atlas_template_fa file
                        The atlas FA to use for regional statistics
  --in_atlas_template_labels file
                        The atlas label image to use for regional statistics
  -o output_dir, --output_dir output_dir
                        Output directory where to save the results
  -g, --graph           Print a graph describing the node connections and exit