nipype.interfaces.cmtk.parcellation module

Parcellate

Link to code

Bases: LibraryBaseInterface

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()                 
Mandatory Inputs:

subject_id (a string) – Subject ID.

Optional Inputs:
  • dilation (a boolean) – Dilate cortical parcels? Useful for fMRI connectivity. (Nipype default value: False)

  • freesurfer_dir (a pathlike object or string representing an existing directory) – Freesurfer main directory.

  • out_roi_file (a pathlike object or string representing a file) – Region of Interest file for connectivity mapping.

  • parcellation_name (‘scale33’ or ‘scale60’ or ‘scale125’ or ‘scale250’ or ‘scale500’) – (Nipype default value: scale500)

  • subjects_dir (a pathlike object or string representing an existing directory) – Freesurfer subjects directory.

Outputs:
  • aseg_file (a pathlike object or string representing an existing file) – Automated segmentation file converted from Freesurfer “subjects” directory.

  • cc_unknown_file (a pathlike object or string representing an existing file) – Image file with regions labelled as unknown cortical structures.

  • dilated_roi_file_in_structural_space (a pathlike object or string representing a file) – Dilated ROI image resliced to the dimensions of the original structural image.

  • ribbon_file (a pathlike object or string representing an existing file) – Image file detailing the cortical ribbon.

  • roi_file (a pathlike object or string representing an existing file) – Region of Interest file for connectivity mapping.

  • roi_file_in_structural_space (a pathlike object or string representing an existing file) – ROI image resliced to the dimensions of the original structural image.

  • roiv_file (a pathlike object or string representing a file) – Region of Interest file for fMRI connectivity mapping.

  • white_matter_mask_file (a pathlike object or string representing an existing file) – White matter mask file.

Parcellate.imports = ('scipy',)
nipype.interfaces.cmtk.parcellation.create_annot_label(subject_id, subjects_dir, fs_dir, parcellation_name)
nipype.interfaces.cmtk.parcellation.create_roi(subject_id, subjects_dir, fs_dir, parcellation_name, dilation)

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

nipype.interfaces.cmtk.parcellation.create_wm_mask(subject_id, subjects_dir, fs_dir, parcellation_name)
nipype.interfaces.cmtk.parcellation.crop_and_move_datasets(subject_id, subjects_dir, fs_dir, parcellation_name, out_roi_file, dilation)
nipype.interfaces.cmtk.parcellation.extract(Z, shape, position, fill)

Extract voxel neighbourhood

Parameters:
  • Z (array-like) – the original data

  • shape (tuple) – tuple containing neighbourhood dimensions

  • position (tuple) – tuple containing central point indexes

  • fill (float) – value for the padding of Z

Returns:

R – the neighbourhood of the specified point in Z

Return type:

ndarray