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This script is for atrophy calculation using Boundary Shift Integral (BSI). 

Usage: niftkAtrophyCalculator.py -in baseline_input_file follow_up_input_file -mask baseline_mask_file follow_up_mask_file -out output_file 

Mandatory Arguments:
 
  -in <f1> <f2>     : are the two input files (f1 baseline and f2 follow-up)
  -out <filename> : is the output file with the computed BSI
  -mask <f1> <f2>   : are the two input brain masks (f1 baseline and f2 follow-up)

Optional Arguments BSI computation:

  -gbsi     : computes BSI using generalized BSI by ... [DEFAULT]
  -knbsi    : computes BSI using K-means BSI by Leung et al. Neuroimage 2010 
  -pbsi     : computes BSI using probabilistic BSI by Ledig et al. MICCAI 2012 
  -pbsig    : computes BSI using probabilistic BSI with gamma=1 as in Ledig et al. MICCAI 2012 
  -sw     : single window BSI, CSF-GM, Freeborough et al. 1997 TMI [DEFAULT]
  -dw     : applies double window BSI, it computes BSI between CSF-GM and WM-GM as in Leung et al. Neuroimage 2010 
  
Optional Arguments:

  -t2     : computes BSI taking into account that we are using T2 images as input data
  -lesion <f1> <f2> : are the two input lesion masks (f1 baseline and f2 follow-up)
  -dil_sub    : number of dilations for lesion masks, useful for lesion substraction. [0-4, by default 1] 
  -sublesion          : substract lesions mask from the brain mask for BSI calculation
  -fill     : activates filling lesions script Declan T. Chard et al. JMRI 2010
  -dil_fill   : number of dilations for lesion masks during the lesion filling. [0-4, by default 0] 
  -roi <f1> <f2>  : are two extra ROI masks for BSI calculation over a specific region like hippocampus (f1 baseline and f2 follow-up)
  -xor <filename>     : outputs file with the XOR region where BSI integral is calculated
  -n3     : apply Boyes et al. Neuroimage 2008 bias field correction method process using N3
  -n4     : apply Boyes et al. Neuroimage 2008 bias field correction method process using N4, mutual exclusive with -n3 argument
  -atlas_mask <filename>: is the mask atlas file (default: /usr/share/fsl/data/standard/MNI152_T1_2mm_brain_mask_dil.nii.gz)
  -atlas_head <filename>: is to the atlas data file (ex: /usr/share/fsl/data/standard/MNI152_T1_2mm.nii.gz)
  -tkn <n>        : number of classes for K-Means [2 or 3, by default 3]
  -dil_kmeans   : number of dilations for K-Means [0-4, by default 3]
  -iso            : transform input images to 1mm isometric voxels
  -debug    : debug mode doesn't delete temporary intermediate images
  -output_dir <path>  : specify the output dir name
  -not_web    : don't open web browser showing results

Recomendations:

  Check that it exists an important overlapping between mask, headmask, head and input file.