interfaces.cmtk.cmtk

CreateMatrix

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Performs connectivity mapping and outputs the result as a NetworkX graph and a Matlab matrix

Example

>>> import nipype.interfaces.cmtk as cmtk
>>> conmap = cmtk.CreateMatrix()
>>> conmap.roi_file = 'fsLUT_aparc+aseg.nii'
>>> conmap.tract_file = 'fibers.trk'
>>> conmap.run()                 

Inputs:

[Mandatory]
resolution_network_file: (an existing file name)
        Parcellation files from Connectome Mapping Toolkit
roi_file: (an existing file name)
        Freesurfer aparc+aseg file
tract_file: (an existing file name)
        Trackvis tract file

[Optional]
count_region_intersections: (a boolean, nipype default value: False)
        Counts all of the fiber-region traversals in the connectivity matrix
        (requires significantly more computational time)
out_endpoint_array_name: (a file name)
        Name for the generated endpoint arrays
out_fiber_length_std_matrix_mat_file: (a file name)
        Matlab matrix describing the deviation in fiber lengths connecting
        each node.
out_intersection_matrix_mat_file: (a file name)
        Matlab connectivity matrix if all region/fiber intersections are
        counted.
out_matrix_file: (a file name)
        NetworkX graph describing the connectivity
out_matrix_mat_file: (a file name, nipype default value: cmatrix.mat)
        Matlab matrix describing the connectivity
out_mean_fiber_length_matrix_mat_file: (a file name)
        Matlab matrix describing the mean fiber lengths between each node.
out_median_fiber_length_matrix_mat_file: (a file name)
        Matlab matrix describing the mean fiber lengths between each node.

Outputs:

endpoint_file: (an existing file name)
        Saved Numpy array with the endpoints of each fiber
endpoint_file_mm: (an existing file name)
        Saved Numpy array with the endpoints of each fiber (in millimeters)
fiber_label_file: (an existing file name)
        Saved Numpy array with the labels for each fiber
fiber_labels_noorphans: (an existing file name)
        Saved Numpy array with the labels for each non-orphan fiber
fiber_length_file: (an existing file name)
        Saved Numpy array with the lengths of each fiber
fiber_length_std_matrix_mat_file: (an existing file name)
        Matlab matrix describing the deviation in fiber lengths connecting
        each node.
filtered_tractographies: (a list of items which are an existing file
         name)
filtered_tractography: (an existing file name)
        TrackVis file containing only those fibers originate in one and
        terminate in another region
filtered_tractography_by_intersections: (an existing file name)
        TrackVis file containing all fibers which connect two regions
intersection_matrix_file: (an existing file name)
        NetworkX graph describing the connectivity
intersection_matrix_mat_file: (an existing file name)
        Matlab matrix describing the mean fiber lengths between each node.
matlab_matrix_files: (a list of items which are an existing file
         name)
matrix_file: (an existing file name)
        NetworkX graph describing the connectivity
matrix_files: (a list of items which are an existing file name)
matrix_mat_file: (an existing file name)
        Matlab matrix describing the connectivity
mean_fiber_length_matrix_mat_file: (an existing file name)
        Matlab matrix describing the mean fiber lengths between each node.
median_fiber_length_matrix_mat_file: (an existing file name)
        Matlab matrix describing the median fiber lengths between each node.
stats_file: (an existing file name)
        Saved Matlab .mat file with the number of fibers saved at each stage

CreateNodes

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Generates a NetworkX graph containing nodes at the centroid of each region in the input ROI file. Node data is added from the resolution network file.

Example

>>> import nipype.interfaces.cmtk as cmtk
>>> mknode = cmtk.CreateNodes()
>>> mknode.inputs.roi_file = 'ROI_scale500.nii.gz'
>>> mknode.run() 

Inputs:

[Mandatory]
resolution_network_file: (an existing file name)
        Parcellation file from Connectome Mapping Toolkit
roi_file: (an existing file name)
        Region of interest file

[Optional]
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_filename: (a file name, nipype default value: nodenetwork.pck)
        Output gpickled network with the nodes defined.

Outputs:

node_network: (a file name)
        Output gpickled network with the nodes defined.

ROIGen

Link to code

Generates a ROI file for connectivity mapping and a dictionary file containing relevant node information

Example

>>> import nipype.interfaces.cmtk as cmtk
>>> rg = cmtk.ROIGen()
>>> rg.inputs.aparc_aseg_file = 'aparc+aseg.nii'
>>> rg.inputs.use_freesurfer_LUT = True
>>> rg.inputs.freesurfer_dir = '/usr/local/freesurfer'
>>> rg.run() 

The label dictionary is written to disk using Pickle. Resulting data can be loaded using:

>>> file = open("FreeSurferColorLUT_adapted_aparc+aseg_out.pck", "r")
>>> file = open("fsLUT_aparc+aseg.pck", "r")
>>> labelDict = pickle.load(file) 
>>> labelDict                     

Inputs:

[Mandatory]
aparc_aseg_file: (an existing file name)
        Freesurfer aparc+aseg file

[Optional]
LUT_file: (an existing file name)
        Custom lookup table (cf. FreeSurferColorLUT.txt)
        mutually_exclusive: use_freesurfer_LUT
freesurfer_dir: (a directory name)
        Freesurfer main directory
        requires: use_freesurfer_LUT
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_dict_file: (a file name)
        Label dictionary saved in Pickle format
out_roi_file: (a file name)
        Region of Interest file for connectivity mapping
use_freesurfer_LUT: (a boolean)
        Boolean value; Set to True to use default Freesurfer LUT, False for
        custom LUT
        mutually_exclusive: LUT_file

Outputs:

dict_file: (a file name)
        Label dictionary saved in Pickle format
roi_file: (a file name)
        Region of Interest file for connectivity mapping

cmat()

Link to code

Create the connection matrix for each resolution using fibers and ROIs.

create_allpoints_cmat()

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Create the intersection arrays for each fiber

create_endpoints_array()

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Create the endpoints arrays for each fiber Parameters ~~~~~~~~~~ fib: the fibers data voxelSize: 3-tuple containing the voxel size of the ROI image Returns ~~~~~~~ (endpoints: matrix of size [#fibers, 2, 3] containing for each fiber the index of its first and last point in the voxelSize volume endpointsmm) : endpoints in milimeter coordinates

create_nodes()

Link to code

get_connectivity_matrix()

Link to code

get_rois_crossed()

Link to code

length()

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Euclidean length of track line

Parameters

xyz : array-like shape (N,3)

array representing x,y,z of N points in a track

along : bool, optional

If True, return array giving cumulative length along track, otherwise (default) return scalar giving total length.

Returns

L : scalar or array shape (N-1,)

scalar in case of along == False, giving total length, array if along == True, giving cumulative lengths.

Examples

>>> xyz = np.array([[1,1,1],[2,3,4],[0,0,0]])
>>> expected_lens = np.sqrt([1+2**2+3**2, 2**2+3**2+4**2])
>>> length(xyz) == expected_lens.sum()
True
>>> len_along = length(xyz, along=True)
>>> np.allclose(len_along, expected_lens.cumsum())
True
>>> length([])
~
>>> length([[1, 2, 3]])
~
>>> length([], along=True)
array([0])

save_fibers()

Link to code

Stores a new trackvis file fname using only given indices