======================== dipy_median_otsu ======================== usage: dipy_median_otsu [-h] [--save_masked] [--median_radius int] [--numpass int] [--autocrop] [--vol_idx [int [int ...]]] [--dilate int] [--out_dir str] [--out_mask str] [--out_masked str] input_files Workflow wrapping the median_otsu segmentation method. Applies median_otsu segmentation on each file found by 'globing' ``input_files`` and saves the results in a directory specified by ``out_dir``. positional arguments: input_files Path to the input volumes. This path may contain wildcards to process multiple inputs at once. optional arguments: -h, --help show this help message and exit --save_masked Save mask --median_radius int Radius (in voxels) of the applied median filter (default 2) --numpass int Number of pass of the median filter (default 5) --autocrop If True, the masked input_volumes will also be cropped using the bounding box defined by the masked data. For example, if diffusion images are of 1x1x1 (mm^3) or higher resolution auto-cropping could reduce their size in memory and speed up some of the analysis. (default False) --vol_idx [int [int ...]] 1D array representing indices of ``axis=-1`` of a 4D `input_volume`. From the command line use something like `3 4 5 6`. From script use something like `[3, 4, 5, 6]`. This input is required for 4D volumes. --dilate int number of iterations for binary dilation (default 'None') output arguments(optional): --out_dir str Output directory (default input file directory) --out_mask str Name of the mask volume to be saved (default 'brain_mask.nii.gz') --out_masked str Name of the masked volume to be saved (default 'dwi_masked.nii.gz') References: Garyfallidis, E., M. Brett, B. Amirbekian, A. Rokem, S. Van Der Walt, M. Descoteaux, and I. Nimmo-Smith. Dipy, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, 1-18, 2014.