interfaces.cmtk.parcellation¶
Parcellate¶
Subdivides segmented ROI file into smaller subregions
This interface implements the same procedure as in the ConnectomeMapper’s parcellation stage (cmp/stages/parcellation/maskcreation.py) for a single parcellation scheme (e.g. ‘scale500’).
Example¶
>>> import nipype.interfaces.cmtk as cmtk
>>> parcellate = cmtk.Parcellate()
>>> parcellate.inputs.freesurfer_dir = '.'
>>> parcellate.inputs.subjects_dir = '.'
>>> parcellate.inputs.subject_id = 'subj1'
>>> parcellate.inputs.dilation = True
>>> parcellate.inputs.parcellation_name = 'scale500'
>>> parcellate.run()
Inputs:
[Mandatory]
subject_id: (a string)
Subject ID
[Optional]
dilation: (a boolean, nipype default value: False)
Dilate cortical parcels? Useful for fMRI connectivity
freesurfer_dir: (an existing directory name)
Freesurfer main directory
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
out_roi_file: (a file name)
Region of Interest file for connectivity mapping
parcellation_name: (u'scale33' or u'scale60' or u'scale125' or
u'scale250' or u'scale500', nipype default value: scale500)
subjects_dir: (an existing directory name)
Freesurfer subjects directory
Outputs:
aseg_file: (an existing file name)
Automated segmentation file converted from Freesurfer "subjects"
directory
cc_unknown_file: (an existing file name)
Image file with regions labelled as unknown cortical structures
dilated_roi_file_in_structural_space: (a file name)
dilated ROI image resliced to the dimensions of the original
structural image
ribbon_file: (an existing file name)
Image file detailing the cortical ribbon
roi_file: (an existing file name)
Region of Interest file for connectivity mapping
roi_file_in_structural_space: (an existing file name)
ROI image resliced to the dimensions of the original structural
image
roiv_file: (a file name)
Region of Interest file for fMRI connectivity mapping
white_matter_mask_file: (an existing file name)
White matter mask file
create_annot_label()
¶
create_roi()
¶
Creates the ROI_%s.nii.gz files using the given parcellation information from networks. Iteratively create volume.
create_wm_mask()
¶
crop_and_move_datasets()
¶
extract()
¶
Extract voxel neighbourhood Parameters ~~~~~~~~~~ Z: the original data shape: tuple containing neighbourhood dimensions position: tuple containing central point indexes fill: value for the padding of Z Returns ~~~~~~~ R: the neighbourhood of the specified point in Z