Defined in file : brainvisa/types/builtin.py
01. DICE calculation (Batch mode) : FFD vs median subsample of volume
[Atlas] Hierarchy Tools
[Binary Volume] Extract Bounding Box (BinaryBoundingBox)
[Binary Volume] Extract Bounding Box from Binary (BoundingBoxCalculation)
[Volume] Connected Component
[Volume] Segment brain from photo (mac)
Average Sulcus Morphological Curves
Binary image: bounding box calculation
Bounding box transformation application
Brainvisa Show Text
Calcul DICE's score on masks/labels volume
Choose best recognition
Cluster detection
Color segmentation: class selection
Color segmentation: feature based classification
Color segmentation: feature based model learning
Color segmentation: model visualization
compute histogram analysis Generic
compute intensity normalization
Compute pairwise distances for a given sulcus
Compute Statistic on Volume ( label or mask )
Compute stats data component
Constellation Group QC table
Constellation Individual QC table
Create an inter subject measures file
Create Ref for Segmentation Quality Control "Notation"
Create Surface-Based Statistical Parametric Maps
custom label volume
Database QC table
Elastix transformation estimation
Extract list of values
Freesurfer / BrainVISA QC table
Freesurfer aparcstats2table
Freesurfer asegstats2table
Generate optimization cartography workflow
GenerateROIAnalysisFiles
Get Functional Signals in Gyrus
Grey level replacement
GreyLevelConversionToActivity
Histology : 3d reconstruction pipeline
Histology: 3D reconstruction pipeline
Hoffman - Compute Coregistration and QC
Hoffman - QC Interface
Import Ecat PET Dynamic & T1MRI
Import volBrain results into a brainvisa database
Labeled volume: calculate the bounding box for each label
Leave-one-out RSS
Merge CSV produced by GE device
Merge DatScan phantom result
Merge Triple Line FWHM results
ml - Factorial design
ml - Fast model generation and testing
ml - Features extraction using feature description file
ml - K Nearest neighbors cross-validation
ml - Logistic regression cross-validation
ml - Logistic regression cross-validation + Classes selection
ml - Multiclass AdaBoost image level cross-validation
ml - Parallel features extraction using feature description file
ml - Parallel multiple images features extraction
ml - Segmentation pipeline
ml - Support Vector Machines cross-validation
ml - Weighted Random Forest
ml - Weighted Random Forest image level cross-validation
ml - Weighted Random Forest image-level cross-validation pipeline
ml - Weighted Random Forest pipeline
ml - Weighting Random Forest (+ cross-validation)
Morphologist CAPSUL iteration
Morphologist QC table
Pairwise Dice computation
Pairwise Distance computation Component
Parallel recognition
Permutatations synthesis
PETScanAtlasAnalysis
QC table of a DARTEL Template
QC table of a DISCO Study
QC table of DARTEL Templates
QC table of DISCO and DARTEL inputs
QC table of DISCO Studies
Recognition Error
Remove Individual Constellation Files
Segmentation Quality Control "Notation"
Single permutation
spm8 - VBM Segmentation - generic
StackingPhotographs
Sulci Curvature Stats
T-test
Transfer Sulci Labels
VolumeROIAnalysis
CSV file
Hierarchy
HTML
JSON file
Minf
PDF File
Python Script
Referential
Soma-Workflow workflow
Text Data Table
Text file
Transformation matrix
XLS file
XLSX file
XML
{center}/{subject}/volBrain/{acquisition}/native/<subject>_native_readme
{center}/{subject}/volBrain/{acquisition}/mni/<subject>_mni_readme
protocol , subject , side , acquisition , filename_variable , sulcus_name , covariate_table , center , analysis , template
phantom , center , acquisition , reconstruction , study , protocol , group_of_subjects , reconstructionTags , sphereDiameter , filename_variable , reconstructionTag
subject , freesurfer_group_of_subjects
modality , manufacturer , device_model , center_device_id , filename_variable
rescan , acquisition_date , time_point , time_duration , center , subject , acquisition , analysis , processing , tracer , description , segmentation_method , PVC_method , Study , from , recons , mapped , contrast , factoriel_design , first_group , second_group , ROIReference , fwhm , labelStat , pet_intersection , nuisance_covariate_list , interest_covariate_list , space , reconstruction , covariateName , graph_version , sulci_recognition_session , manually_labelled , automatically_labelled , ROI_name , volumeStat , Template , side , best , VOIReference , template , ROIStat , VOIStatistic , filename_variable , covariate_table_id , sulcus_name , group_of_subjects , method , studyname , gyrus , smoothing , sid , smallerlength , greaterlength , study , covariate_table , group_name , atlas , research_group , subject_age , bin_unit , pet_tracer , pet_acquisition , modality , assessment_type , atlasname , reconDiam , statLabel , factorial_design , contrast_type , contrast_index , basename , reconstruction_diameter
filename_variable , side , sulci_database , sulci_segments_model_type , atlas , VOIReference , VOIStatistic , atlasname
protocol , subject , from , center , acquisition , tracer , reconstruction , analysis , ROIReference , covariateName , graph_version , sulci_recognition_session , side , manually_labelled , automatically_labelled , best , ROIStat , filename_variable , sulcus_name , covariate_table , group_of_subjects , template , reconDiam