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.


input_files : string
Path to the input volumes. This path may contain wildcards to process multiple inputs at once.
save_masked : bool
Save mask
median_radius : int, optional
Radius (in voxels) of the applied median filter (default 2)
numpass : int, optional
Number of pass of the median filter (default 5)
autocrop : bool, optional
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 : variable int, optional
1D array representing indices of axis=3 of a 4D input_volume ‘None’ (the default) corresponds to (0,) (assumes first volume in 4D array). From cmd line use 3 4 5 6. From script use [3, 4, 5, 6].
dilate : int, optional
number of iterations for binary dilation (default ‘None’)
out_dir : string, optional
Output directory (default input file directory)
out_mask : string, optional
Name of the mask volume to be saved (default ‘brain_mask.nii.gz’)
out_masked : string, optional
Name of the masked volume to be saved (default ‘dwi_masked.nii.gz’)