Code: file:///tmp/buildd/nipype-0.5.3/nipype/workflows/fmri/spm/preprocess.py#L224
Create a vbm workflow that generates DARTEL-based template
>>> preproc = create_DARTEL_template()
>>> preproc.inputs.inputspec.structural_files = [os.path.abspath('s1.nii'), os.path.abspath('s3.nii')]
>>> preproc.inputs.inputspec.template_prefix = 'Template'
>>> preproc.run()
Inputs:
inputspec.structural_files : structural data to be used to create templates
inputspec.template_prefix : prefix for dartel template
Outputs:
outputspec.template_file : DARTEL template
outputspec.flow_fields : warps from input struct files to the template
Code: file:///tmp/buildd/nipype-0.5.3/nipype/workflows/fmri/spm/preprocess.py#L15
Create an spm preprocessing workflow with freesurfer registration and artifact detection.
The workflow realigns and smooths and registers the functional images with the subject’s freesurfer space.
>>> preproc = create_spm_preproc()
>>> preproc.base_dir = '.'
>>> preproc.inputs.inputspec.fwhm = 6
>>> preproc.inputs.inputspec.subject_id = 's1'
>>> preproc.inputs.inputspec.subjects_dir = '.'
>>> preproc.inputs.inputspec.functionals = ['f3.nii', 'f5.nii']
>>> preproc.inputs.inputspec.norm_threshold = 1
>>> preproc.inputs.inputspec.zintensity_threshold = 3
Inputs:
inputspec.functionals : functional runs use 4d nifti
inputspec.subject_id : freesurfer subject id
inputspec.subjects_dir : freesurfer subjects dir
inputspec.fwhm : smoothing fwhm
inputspec.norm_threshold : norm threshold for outliers
inputspec.zintensity_threshold : intensity threshold in z-score
Outputs:
outputspec.realignment_parameters : realignment parameter files
outputspec.smoothed_files : smoothed functional files
outputspec.outlier_files : list of outliers
outputspec.outlier_stats : statistics of outliers
outputspec.outlier_plots : images of outliers
outputspec.mask_file : binary mask file in reference image space
outputspec.reg_file : registration file that maps reference image to
freesurfer space
outputspec.reg_cost : cost of registration (useful for detecting misalignment)
Code: file:///tmp/buildd/nipype-0.5.3/nipype/workflows/fmri/spm/preprocess.py#L131
Create a vbm workflow that generates DARTEL-based warps to MNI space
Based on: http://www.fil.ion.ucl.ac.uk/~john/misc/VBMclass10.pdf
>>> preproc = create_vbm_preproc()
>>> preproc.inputs.inputspec.fwhm = 8
>>> preproc.inputs.inputspec.structural_files = [os.path.abspath('s1.nii'), os.path.abspath('s3.nii')]
>>> preproc.inputs.inputspec.template_prefix = 'Template'
>>> preproc.run()
Inputs:
inputspec.structural_files : structural data to be used to create templates
inputspec.fwhm: single of triplet for smoothing when normalizing to MNI space
inputspec.template_prefix : prefix for dartel template
Outputs:
outputspec.normalized_files : normalized gray matter files
outputspec.template_file : DARTEL template
outputspec.icv : intracranial volume (cc - assuming dimensions in mm)