NAME

       CreateDTICohort - part of ANTS registration suite

DESCRIPTION

   COMMAND:
              CreateDTICohort

              CreateDTICohort  implements  the work of Van Hecke et al. (On the construction of a
              ground truth framework for evaluating  voxl-based  diffusion  tensor  MRI  analysis
              methods,  Neuroimage  46:692-707, 2009) to create simulated DTI data sets. The only
              difference is that all registrations (both for the input  population  and  for  the
              output population) are assumed to take place outside of this program.

   OPTIONS:
       -d, --image-dimensionality 2/3

              This option forces the image to be treated as a specified-dimensional image. If not
              specified, the program tries to infer the dimensionality from the input image.

       -a, --dti-atlas inputDTIAtlasFileName

              A diffusion tensor atlas image is required input for creating the cohort.

       -x, --label-mask-image maskImageFileName
              lowerThresholdFunction

              A mask image can  be  specified  which  determines  the  region(s).  to  which  the
              simulated  pathology operations are applied. See also the option '--pathology'.  If
              no mask is specified one is created by thresholding the atlas FA map at 0.2  unless
              a lower threshold is specified.

       -n, --noise-sigma <noiseSigma=18>

              This  parameter characterizes the Rician noise in the original DWIimages. Van Hecke
              uses the noise-estimation method of Sijbers et al.  "Automatic  estimation  of  the
              noise variance from the histogram of a magnetic resonance image", Phys.  Med. Biol.
              52:1335-1348, 2007.

       -p,                                                                            --pathology
              label[<percentageChangeEig1=-0.05>,<percentageChangeAvgEig2andEig3=0.05>,<numberOfVoxels=all
              or percentageOfvoxels>]

              The user can specify the simulated pathology in a given area using  a  label  mask.
              If no label is prepended to parameters, the specified parameters are applied to all
              labels.Pathology is simulated by changing the eigenvalues. Typically this  involves
              a  decrease  in  the  largest  eigenvalue  and  an  increase  in the average of the
              remaining  eigenvalues.  Change  is  specified  as  a  percentage  of  the  current
              eigenvalues.  However,  care  is  taken to ensure that diffusion direction does not
              change. Additionally, one can specify the number of voxels affected in each  region
              or  one  can  specify  the  percentage of voxels affected. Default is to change all
              voxels. Note that the percentages  must  be  specified  in  the  range  [0,1].  For
              dimension=3  where  the  average transverse diffusion eigenvalues are altered, this
              change is propagated to the distinct eigenvalues by forcing the  ratio  to  be  the
              same before the change.

       -w, --dwi-parameters [B0Image,directionFile,bvalue]
              [B0Image,schemeFile]

              This  option  specifies  the  parameters  of  the  output diffusion-weighted images
              including the directions  and  b-values.  The  directions  are  specified  using  a
              direction file which has as its first line the number of directions.Each successive
              three lines contains the x,  y,  and  z  directions,  respectively,  and  a  single
              b-value.  Note that several direction files of this format are distributed with the
              Camino                                 DTI                                  toolkit
              (http://web4.cs.ucl.ac.uk/research/medic/camino/pmwiki/pmwiki.php).  Alternatively,
              one can specify a scheme file where each  direction  is  specified  followed  by  a
              b-value    for    that    direction,    i.e.   <x1>   <y1>   <z1>   <bvalue1>   ...
              <xN><yN><zN><bvalueN>.

       -r, --registered-population textFileWithFileNames.txt

              If one wants to introduce inter-subject variabilitya registered DTI  population  to
              the  DTI atlas is required. This variability is modeled by a PCA decomposition on a
              combination of the first eigenvalue image and the average of the second  and  third
              eigenvalues.The  registered  image file names are specified using a text file where
              each line is the name of an individual DTI.

       -o,                                                                               --output
              [outputDirectory,fileNameSeriesRootName,<numberOfControls=10>,<numberOfExperimentals=10>]

              The output consists of a set of diffusion-weighted images for  each  subject.  Each
              file  name  is  prepended  with the word 'Control' or 'Experimental'. The number of
              control and experimental subjects can be also be specified  on  the  command  line.
              Default is 10 for each group.

       -h

              Print the help menu (short version).  <VALUES>: 0

       --help

              Print the help menu.  <VALUES>: 1, 0