functionalLungSegmentation: Ventilation-based segmentation of hyperpolarized gas lung...

In neuroconductor-devel/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

Description

Lung segmentation into classes based on ventilation as described in this paper:

Usage

functionalLungSegmentation(
  image,
  mask,
  numberOfIterations = 2,
  numberOfAtroposIterations = 5,
  mrfParameters = "[0.7,2x2x2]",
  numberOfClusters = 6,
  clusterCenters = NA,
  biasCorrection = "n4",
  verbose = TRUE
)

Arguments

image	input proton-weighted MRI.
mask	mask image designating the region to segment. 0/1 = background/foreground.
numberOfIterations	number of Atropos <–> bias correction iterations (outer loop).
numberOfAtroposIterations	number of Atropos iterations (inner loop). If numberOfAtroposIterations = 0, this is equivalent to K-means with no MRF priors.
mrfParameters	parameters for MRF in Atropos.
numberOfClusters	number of tissue classes (default = 4)
clusterCenters	initialization centers for k-means
biasCorrection	apply n3, n4, or no bias correction (default = "n4").
verbose	print progress to the screen.

Details

https://pubmed.ncbi.nlm.nih.gov/21837781/

Value

segmentation image, probability images, and processed input image.

Author(s)

Tustison NJ

Examples

## Not run: 

library( ANTsR )

image <- antsImageRead( "lung.nii.gz" )
mask <- antsImageRead( "mask.nii.gz" )
output <- functionalLungSegmentation( image, mask )
antsImageWrite( output$segmentationImage, "outputSegmentation.nii.gz" )


## End(Not run)

neuroconductor-devel/ANTsR documentation built on April 1, 2021, 1:02 p.m.