Constellation Individual Pipeline - Connectomist

A pipeline to process Connectomist data of a subject into an individual connectivity matrix compatible with Constellation requirements.


A complete pipeline: an intra_subject chain which builds the individual connectivity matrices for a given input "patch" (gyrus, or large region) of the brain. The preprocessings are done using FreeSurfer for the anatomical data, and Connectomist for the diffusion data.

The method implemented here is described in:

S. Lefranc, P. Roca, M. Perrot, C. Poupon, D. Le Bihan, J.-F. Mangin, and D. Rivière. Groupwise connectivity-based parcellation of the whole human cortical surface using watershed-driven dimension reduction. Medical Image Analysis, 30:11-29, 2016. [bibtex-entry]

To parcellate the whole brain, this process has to be iterated over all gyri.

Usage example

regions_nomenclature:            /casa/build/share/brainvisa-share-4.6/nomenclature/translation/nomenclature_desikan_freesurfer.txt
outputs_database:                /my/path/brainvisa_db 
study_name:                      studyA  
method:                          averaged approach  
region:                          lh.inferiorparietal
subject_indir:                   /my/path/connectomist_db/B1500/StreamlineProbabilistic/aQBI/27seeds/001
individual_white_mesh:           /my/path/freesurfer_db/001/surf/bh.r.aims.white.gii
dw_to_t1:                        /my/path/connectomist_db/B1500/StreamlineProbabilistic/aQBI/27seeds/001/dw_to_t1.trm
regions_parcellation:            /my/path/freesurfer_db/group_analysis/average_group/average_brain/bh.annot.averagebrain.gii
regions_selection:               Custom
keep_regions:                    'lh.unknown' 'lh.bankssts' 'lh.inferiorparietal'
fiber_tracts_format:             bundles
min_fibers_length:               20.0  
max_fibers_length:               500.0  
smoothing:                       3.0  
kmax:                            12  
normalize:                       True  
erase_matrix:                    True  


regions_nomenclature: Nomenclature ROIs File ( input )
Nomenclature of the cortical parcellation used to partition the study.
Example : Freesurfer Desikan_Killiany Atlas
outputs_database: Choice ( input )
This parameter retrieves all databases with brainvisa ontology present in your configuration, the generated files will be written on the chosen one (see the documentation to add a database in the BrainVisa configuration).
study_name: OpenChoice ( input )
General name of the study.
method: Choice ( input )
Two methods are proposed:
(1) averaged approach to obtain an average result on the group.
(2) concatenated approach to obtain individual results across the group.
region: OpenChoice ( input )
The study region based on regions_nomenclature file.
subject_indir: Subject ( input )
Subjects directory in a Connectomist database, where the fiber tracts files can be found.
individual_white_mesh: White Mesh ( input )
Freesurfer white-grey interface of the cortex.
Should not be inflated.
dw_to_t1: Transform T2 Diffusion MR to Raw T1 MRI ( input )
Affine spatial transformation to get the T1 MRI space from the dMRI diffusion (and tracts) space.
regions_parcellation: ROI Texture ( input )
Cortical parcellation used to partition the study.
Example : Freesurfer Desikan_Killiany Atlas (?h.aparc.annot).
regions_selection: Choice ( input )
This parameter can be used to exclude some regions from the data analysis. This is useful to study the specific connectivity between a given set of regions, or to exclude the initial patch region.
keep_regions: ListOf( OpenChoice ) ( input )
Kept regions for the data analysis.
fiber_tracts_format: Choice ( input )
Different fiber tracts formats are supported.
Selectable formats are:
(1) TrackVis file format with .trk as filename extension.
(2) Connectomist file format with .bundles as filename extension.
min_fibers_length: Float ( input )
A filtering parameter to exclude low length fibers. Default to 20mm.
max_fibers_length: Float ( input )
A filtering parameter to exclude long length fibers. Default to 500mm.
smoothing: Float ( input )
Degree of smoothing (in millimetres).
Default to 3.0 mm.
kmax: Integer ( input )
Maximal number of clusters used to parcellate the study region.
Default to 12.
normalize: Boolean ( input )
By default the connectivity matrices values are normalized to balance any spurious weighting effects due to more connected regions or subjects, or to the tractography algorithm (number of seeds...). But sometimes we also like to see the raw connectivity matrix: in that case, uncheck this normalization.
erase_smoothed_matrix: Boolean ( input )

Technical information

Toolbox : Constellation

User level : 1

Identifier : constel_individual_pipeline

File name : brainvisa/toolboxes/constellation/processes/individual_pipelines/

Supported file formats :

regions_nomenclature :
Text file, Text file
subject_indir :
Directory, Directory
individual_white_mesh :
GIFTI file, GIFTI file, MESH mesh, MNI OBJ mesh, PLY mesh, TRI mesh
dw_to_t1 :
Transformation matrix, Transformation matrix
regions_parcellation :
GIFTI file, GIFTI file, Texture