interfaces.cmtk.parcellation

Parcellate

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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: ('scale33' or 'scale60' or 'scale125' or
         'scale250' or '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()

Link to code

create_roi()

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Creates the ROI_%s.nii.gz files using the given parcellation information from networks. Iteratively create volume.

create_wm_mask()

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crop_and_move_datasets()

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extract()

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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