niftkMTPFillLesions.py

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This script is for multi-modality and multi-time-point lesion filling using the patch-based method Prados et al. MICCAI 2014. 

Usage: niftkMTPFillLesions.py -in <filename> [optional arguments]

Mandatory Arguments:
 
  -in <filename>      : is the text input file with the absolute path to the image, lesion, output file and skull stripped [optional] files for each time-point and modality. Ex:
        /path/to/image_1.nii.gz /path/to/lesions_1.nii.gz /path/to/output_1.nii.gz /path/to/skull_stripped_image_1.nii.gz
        /path/to/image_2.nii.gz /path/to/lesions_2.nii.gz /path/to/output_2.nii.gz /path/to/skull_stripped_image_2.nii.gz
        ...
        /path/to/image_N.nii.gz /path/to/lesions_N.nii.gz /path/to/output_N.nii.gz /path/to/skull_stripped_image_N.nii.gz

Optional Arguments:

  -atlas <filename> : is the path to the atlas data file, use only if you don't specify skull-stripped mask.
  -atlas_mask <filename>: is the path to the mask atlas file, use only if you don't specify skull-stripped mask.
  -debug    : debug mode doesn't delete temporary intermediate images.
  -output_dir <path>  : specify the output dir name in case that we are working with relative path.
  
Optional Fill Lesions Arguments:

  -dil    <int>   : number of dilations for lesion masks (by default 0).
  -match  <float>       : percentage of minimum number of voxels between patches <float> (by default 0.5).
  -search <float>       : minimum percentage of valid voxels in target patch <float> (by default 0).
  -smo    <float>       : smoothing by <float> (in minimal 6-neighbourhood voxels (by default 0.1)).
  -size   <int>         : search regions size respect biggest patch size (by default 4).