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

functionalLungSegmentation(
  image,
  mask,
  numberOfIterations = 1,
  numberOfAtroposIterations = 0,
  mrfParameters = "[0.3,2x2x2]",
  verbose = TRUE
)

Arguments

image

input proton-weighted MRI.

mask

mask image designating the region to segment. 0/1 = background/foreground.

numberOfIterations

number of Atropos <--> N4 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.

verbose

print progress to the screen.

Value

segmentation image, probability images, and processed input image.

Details

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

Examples

if (FALSE) { library( ANTsR ) image <- antsImageRead( "lung.nii.gz" ) mask <- antsImageRead( "mask.nii.gz" ) output <- functionalLungSegmentation( image, mask ) antsImageWrite( output$segmentationImage, "outputSegmentation.nii.gz" ) }