Difference between revisions of "Groupwise registration using DTI-TK"
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The python script to run a groupwise of diffusion tensor image (DTI) is <code>perform_dti_groupwise.py</code> | The python script to run a groupwise of diffusion tensor image (DTI) is <code>perform_dti_groupwise.py</code> | ||
| + | To use this script [[Prerequisite DTI-TK | DTI-TK has to be installed]] | ||
| − | To generate tensor images from the diffusion MRI data, see the [[DTI processing]] page. | + | To generate tensor images from the diffusion MRI data, see the [[DTI pre-processing]] page. |
The script help is the following: | The script help is the following: | ||
Latest revision as of 12:49, 25 August 2015
The python script to run a groupwise of diffusion tensor image (DTI) is perform_dti_groupwise.py
To use this script DTI-TK has to be installed
To generate tensor images from the diffusion MRI data, see the DTI pre-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(orDTI_filename_trans.affif the number of nonlinear iteration is set to zero)
- the input image rescaled to be used by dtitk:
