Difference between revisions of "Groupwise registration using DTI-TK"

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As an input, the script expects several DTI images, e.g. <code>/folder/DTI_img0.nii.gz</code>, <code>/folder/DTI_img1.nii.gz</code>, ..., <code>/folder/DTI_imgN.nii.gz</code> and can be run as:
 
As an input, the script expects several DTI images, e.g. <code>/folder/DTI_img0.nii.gz</code>, <code>/folder/DTI_img1.nii.gz</code>, ..., <code>/folder/DTI_imgN.nii.gz</code> and can be run as:
<pre>perform_dti_groupwise.py --input_img /folder/DTI_img0.nii.gz /folder/DTI_img1.nii.gz [...] /folder/DTI_imgN.nii.gz</pre>
+
<pre>python perform_dti_groupwise.py --input_img /folder/DTI_img0.nii.gz /folder/DTI_img1.nii.gz [...] /folder/DTI_imgN.nii.gz</pre>
  
 
Alternatively, one can only specify the folder containing all the input images, e.g.:
 
Alternatively, one can only specify the folder containing all the input images, e.g.:
  
<pre>perform_dti_groupwise.py --input_dir /folder</pre>
+
<pre>python perform_dti_groupwise.py --input_dir /folder</pre>
  
 
in which case all the image files (analyze and nifti) in <code>/folder</code> will be considered.
 
in which case all the image files (analyze and nifti) in <code>/folder</code> will be considered.
Line 42: Line 42:
 
By default the output of the script will be written in the current directory, the use can specify the output directory by using the <code>--output_dir</code> option, e.g.:
 
By default the output of the script will be written in the current directory, the use can specify the output directory by using the <code>--output_dir</code> option, e.g.:
  
<pre>perform_dti_groupwise.py --input_dir /folder --output_dir /output_directory</pre>
+
<pre>python perform_dti_groupwise.py --input_dir /folder --output_dir /output_directory</pre>
  
 
The number of iteration for the rigid, affine and non-rigid steps are 3, 3 and 6 respectively as recommended in DTITK. This can be altered using the <code>--rigid_it</code>, <code>--affine_it</code> and <code>--nonrigid_it</code> arguments, e.g.:
 
The number of iteration for the rigid, affine and non-rigid steps are 3, 3 and 6 respectively as recommended in DTITK. This can be altered using the <code>--rigid_it</code>, <code>--affine_it</code> and <code>--nonrigid_it</code> arguments, e.g.:
<pre>perform_dti_groupwise.py --input_dir /folder --output_dir /output_directory --rigid_it 1 --affine_it 1 --nonlinear_it 1</pre>
+
<pre>python perform_dti_groupwise.py --input_dir /folder --output_dir /output_directory --rigid_it 1 --affine_it 1 --nonlinear_it 1</pre>
 
Note that the sum of rigid and affine iteration can not be equal to zero.
 
Note that the sum of rigid and affine iteration can not be equal to zero.
  

Revision as of 15:48, 20 August 2015

The python script to run a groupwise of diffusion tensor image (DTI) is perform_dti_groupwise.py

To generate tensor images from the diffusion MRI data, see the DTI processing page.

The script help is the following:

usage: perform_dti_groupwise.py [-h]
                                [--input_dir input_dir | --input_img input_img [input_img ...]]
                                [--rigid_it number] [--affine_it number]
                                [--nonrigid_it number] -o output_dir [-g]

Groupwise registration for DTI images

optional arguments:
  -h, --help            show this help message and exit
  --input_dir input_dir
                        Input directory containing the Nifti file(s) to
                        include in the processing
  --input_img input_img [input_img ...]
                        List of Nifti file(s) to include in the processing
  --rigid_it number     Number of iteration to perform for the rigid step
                        (default is 3)
  --affine_it number    Number of iteration to perform for the affine step
                        (default is 3)
  --nonrigid_it number  Number of iteration to perform for the nonrigid step
                        (default is 6)
  -o output_dir, --output_dir output_dir
                        Output directory where to save the results
  -g, --graph           Print a graph describing the node connections and exit

As an input, the script expects several DTI images, e.g. /folder/DTI_img0.nii.gz, /folder/DTI_img1.nii.gz, ..., /folder/DTI_imgN.nii.gz and can be run as:

python perform_dti_groupwise.py --input_img /folder/DTI_img0.nii.gz /folder/DTI_img1.nii.gz [...] /folder/DTI_imgN.nii.gz

Alternatively, one can only specify the folder containing all the input images, e.g.:

python perform_dti_groupwise.py --input_dir /folder

in which case all the image files (analyze and nifti) in /folder will be considered.

By default the output of the script will be written in the current directory, the use can specify the output directory by using the --output_dir option, e.g.:

python perform_dti_groupwise.py --input_dir /folder --output_dir /output_directory

The number of iteration for the rigid, affine and non-rigid steps are 3, 3 and 6 respectively as recommended in DTITK. This can be altered using the --rigid_it, --affine_it and --nonrigid_it arguments, e.g.:

python perform_dti_groupwise.py --input_dir /folder --output_dir /output_directory --rigid_it 1 --affine_it 1 --nonlinear_it 1

Note that the sum of rigid and affine iteration can not be equal to zero.

The outputs of the script are the following:

  • An average template image called: dtitk_groupwise_template.nii.gz
  • For every input image, name for example with the following pattern DTI_filename.nii.gz:
    • the input image rescaled to be used by dtitk: DTI_filename_scaled.nii.gz
    • the scale image warped to the template space: DTI_filename_warped.nii.gz
    • the transformation use to resample the scale image to the template space: DTI_filename_trans.nii.gz (or DTI_filename_trans.aff if the number of nonlinear iteration is set to zero)