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ANTs DiReCT Cortical Thickness (KellyKapowski)

Library: ANTs | Docker Image: antsx/ants

Function

Estimates cortical thickness using the DiReCT algorithm from segmentation data.

Modality: Tissue segmentation image plus GM and WM probability maps (3D NIfTI).

Typical Use: Computing cortical thickness from pre-existing tissue segmentation.

Key Parameters

-d (dimension), -s (segmentation image), -g (GM probability), -w (WM probability), -o (output thickness map), -c (convergence)

Key Points

Core thickness estimation engine used by antsCorticalThickness.sh. Requires good segmentation as input.

Inputs

Name Type Required Label Flag
dimensionality int Yes Image dimensionality (2 or 3) -d
segmentation_image File Yes Segmentation image with labeled tissues -s
gray_matter_prob File Yes Gray matter probability image -g
white_matter_prob File Yes White matter probability image -w
output_image string Yes Output cortical thickness image -o
convergence string No Convergence parameters [iterations,convergenceThreshold,thicknessPrior] -c
thickness_prior double No Prior estimate for cortical thickness -t
gradient_step double No Gradient descent step size -r
smoothing_sigma double No Gradient field smoothing parameter -m
number_integration_points int No Number of integration points -n
verbose boolean No Enable verbose output -v

Accepted Input Extensions

  • segmentation_image: .nii, .nii.gz
  • gray_matter_prob: .nii, .nii.gz
  • white_matter_prob: .nii, .nii.gz

Outputs

Name Type Glob Pattern
thickness_image File $(inputs.output_image)
log File KellyKapowski.log

Output Extensions

  • thickness_image: .nii, .nii.gz

Docker Tags

Available versions: latest, master, v2.6.5, 2.6.5, v2.6.4, 2.6.4, v2.6.3, 2.6.3, v2.6.2, 2.6.2 and 5 more

Categories

  • Structural MRI > ANTs > Cortical Thickness

Documentation

Official Documentation