Cortical thickness (advection)

Compute the cortical thickness along Laplace field lines from a classification volume, using Eulerian advection (slightly more precise than upwinding, but much slower)

Paramètres

classif: Any Type ( entrée )

classification image of the cortex (100 inside, 0 in CSF, 200 in white matter)

verbosity: Entier ( optional, input )

Verbosity level

laplace_precision: Nombre ( optional, input )

target maximum relative error in first-order finite differences

laplace_typical_cortical_thickness: Nombre ( optional, input )

typical thickness of the cortex (mm), used for accelerating convergence

advection_step_size: Nombre ( optional, input )

size of the advection step (millimetres)

advection_max_dist: Nombre ( optional, input )

maximum advection distance (millimetres)

equidistant_depth: String ( optional, input )

thickness_image: Any Type ( sortie )

result of the arithmetic

use_capsul_completion: Booléen ( input )

edit_pipeline: Booléen ( input )

capsul_gui: Booléen ( input )

edit_study_config: Booléen ( input )

Informations techniques

Toolbox : highres-cortex

Niveau d'utilisateur : 1

Identifiant : thickness_adv

Nom de fichier : brainvisa/toolboxes/highres_cortex/processes/thickness_adv.py

Supported file formats :

classif :

Répertoire, BMP image, Répertoire, ECAT i image, ECAT v image, Fichier, GIF image, GIS image, JPEG image, MINC image, MNG image, NIFTI-1 image, PBM image, PGM image, PNG image, PPM image, SPM image, TIFF image, TIFF(.tif) image, VIDA image, XBM image, XPM image, gz compressed MINC image, gz compressed NIFTI-1 image

thickness_image :

Répertoire, BMP image, Répertoire, ECAT i image, ECAT v image, Fichier, GIF image, GIS image, JPEG image, MINC image, MNG image, NIFTI-1 image, PBM image, PGM image, PNG image, PPM image, SPM image, TIFF image, TIFF(.tif) image, VIDA image, XBM image, XPM image, gz compressed MINC image, gz compressed NIFTI-1 image