02. Template building

This is an internal component, see Disco pipeline for general information.

Description

This step creates a template based on the sulcal imprints of input subjects, by computing a deformation from each subject to the template and iteratively refining the template using the registered imprints.

Outputs of this step are the deformed sulcal imprints for each subject.

This process uses a hidden input: the imprint_workspace.mat file of each subject, which are output by 01. Sulcal imprints extraction. It also has other outputs, which are not shown at the level of the BrainVISA process:

Here is a complete list:
DISCO_{Study}
├── figures
│   ├── Hausdorff_Mean_Distances_*.fig
│   └── Hausdorff_Mean_Distances_final.fig
├── mat
│   ├── res_suj_*_*.mat
│   ├── subject_def_*_*.mat
│   ├── template_elaboration_*.mat
│   └── template_elaboration_complete.mat
└── templates
    ├── template_visu_*_L.mesh
    ├── template_visu_*_L.mesh
    ├── template_visu_*_L.tex
    └── template_visu_*_R.tex

Paramètres

anatomical_constraints: Choice ( input )
study_dir: DISCO Study Dir ( entrée )
left_imprint_mesh: ListOf( Sulcal Imprint Full Mesh ) ( input )
sulci_to_be_studied: Sulci To Be Studied DISCO ( entrée )
bundles_to_be_studied: Bundles To Be Studied DISCO ( optional, entrée )
left_imprint_def_mesh: ListOf( Sulcal Imprint Def Full Mesh ) ( output )
Left sulcal imprints of all subjects transformed into the common space.
left_imprint_def_texture: ListOf( Sulcal Imprint Def Full Texture ) ( output )
right_imprint_def_mesh: ListOf( Sulcal Imprint Def Full Mesh ) ( output )
Right sulcal imprints of all subjects transformed into the common space.
right_imprint_def_texture: ListOf( Sulcal Imprint Def Full Texture ) ( output )
couple_weight_type: Choice ( input )
Method used for assigning a weight to the different sulcal constraints. Please look at the MATLAB code to see what it does exactly.
nbMin: Entier ( input )
Number of minimizations to be performed for estimating the deformations. For example nbMin=3 will instruct the algorithm to do 3 consecutive minimizations, decreasing the size of the point matching kernels sigmaW and sigmaI after each of them.
coefK: Réel ( input )
Adjustment factor for the automatic computation of the Fast Gauss Transform precision coefficient K.
coef_sigV: Réel ( input )
The kernel size which defines the scale of deformation, in millimetres. In other words, the deformation kernel is a function of the Euclidean distance between two points divided by coef_sigV.
check_outliers: Booléen ( input )
If enabled, outlier imprints will be detected and excluded from the data before the template is created. Outlier detection and exclusion is done at the level of each imprint for each subject.
threshold_outliers: Réel ( input )
Threshold used for outlier detection: each imprint that has a higher Z-score will be excluded. Outlier detection and exclusion is done at the level of each imprint for each subject.

Informations techniques

Toolbox : Disco

Niveau d'utilisateur : 1

Identifiant : buildTemplate

Nom de fichier : brainvisa/toolboxes/disco/processes/DISCO_components/buildTemplate.py

Supported file formats :

study_dir :
Répertoire, Répertoire
left_imprint_mesh :
MESH mesh, MESH mesh
sulci_to_be_studied :
Text file, Text file
bundles_to_be_studied :
Text file, Text file
left_imprint_def_mesh :
MESH mesh, MESH mesh
left_imprint_def_texture :
Texture, Texture
right_imprint_def_mesh :
MESH mesh, MESH mesh
right_imprint_def_texture :
Texture, Texture