Each of these output images was created in this step:
- whole brain ROI mask
- brain only T1 image
- whole brain probability mask
- extraction mask (ROI mask dilated 28 vox)
- registration mask (ROI mask dilated 18 vox)
- 6 tissue segmentation
- six tissue priors
ANTs Cortical Thickness pipeline could then be run using the population-based template that was generated earlier. The code below is extremely similar to that of ANTs cortical thickness in the previous step, but uses the output files created in that job script.
antsCorticalThickness.sh \
-d 3 -a <path/to/resampled.nii.gz> \
-e <population/based/template.nii.gz> \
-t <template_BrainCerebellum.nii.gz> \
-m <template_BrainCerebellumProbabilityMask.nii.gz> \
-f <template_BrainCerebellumExtractionMask.nii.gz> \
-p <priors%d.nii.gz> \
-q 1 -o <output/directory>
The -d option indicates dimensionality. There are a variety of indicators for which input file is being directed to in which spot, options -a through -p in the code above.
Statistical Analyses
In order to prepare the images to be analyzed using a program called randomise, the images had to go through a few additional processing steps.
Randomise runs using one 4D image, so all of the images in the data set had to be merged into one 4D image.