Python script to perform the spatially constrained parcellation of functional MRI data as described in Craddock et al., Human Brain Mapp., 33 (9) 2012
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.travis.yml
README
README.md
__init__.py
binfile_parcellation.py
gpl-3.0.txt
group_binfile_parcellation.py
group_mean_binfile_parcellation.py
harvardoxford_cortical_labels.csv
harvardoxford_subcortical_labels.csv
juelich_labels.csv
make_image_from_bin.py
make_image_from_bin_renum.py
make_local_connectivity_ones.py
make_local_connectivity_scorr.py
make_local_connectivity_tcorr.py
mni_labels.csv
parcel_naming.py
pyClusterROI_test.py
python_ncut_lib.py
scorr_test.py
talairach_labels.csv
tcorr_test.py

README.md

DOI pyClusterROI

Copyright (C) 2010 R. Cameron Craddock (cameron.craddock@gmail.com)

This is the pyClusterROI python toolbox for the spatially constrained clustering of fMRI data.

For more information refer to:

Craddock, R. C.; James, G. A.; Holtzheimer, P. E.; Hu, X. P. & Mayberg, H. S. A whole brain fMRI atlas generated via spatially constrained spectral clustering Human Brain Mapping, 2012, 33, 1914-1928 doi: 10.1002/hbm.21333..

 @ARTICLE{Craddock2012,
   author = {Craddock, R C and James, G A and Holtzheimer, P E and Hu, X P and
   Mayberg, H S},
   title = {{A whole brain fMRI atlas generated via spatially constrained
   spectral clustering}},
   journal = {Human Brain Mapping},
   year = {2012},
   volume = {33},
   pages = {1914--1928},
   number = {8},
   address = {Department of Neuroscience, Baylor College of Medicine, Houston,
       TX, United States},
   pmid = {21769991},
 } 

Documentation, updated source code and other information can be found at the NITRC web page: http://www.nitrc.org/projects/cluster_roi/ and on github at https://github.com/ccraddock/cluster_roi

This library requires NumPy, SciPy, and NiBabel.

Please refer to pyClusterROI_test.py for detailed instructions on how to use the code. This script can be executed using test data.