spatial prior-based image segmentation.

markov random field regularized, prior-based image segmentation that is a wrapper around atropos (see ANTs and related publications).

priorBasedSegmentation(
  img,
  priors,
  mask,
  priorWeight = 0.25,
  mrf = 0.1,
  iterations = 25,
  verbose = FALSE
)

Arguments

img

input image or image list for multivariate segmentation

priors

list of priors that cover the number of classes

mask

segment inside this mask

priorWeight

usually 0 (priors used for initialization only), 0.25 or 0.5.

mrf

regularization, higher is smoother, a numerical value in range 0.0 to 0.2

iterations

maximum number of iterations. could be a large value eg 25.

verbose

maximum number of iterations. could be a large value eg 25.

Value

segmentation and probability images

Author

Brian B. Avants

Examples

fi <- antsImageRead(getANTsRData("r16"))
seg <- kmeansSegmentation(fi, 3)
msk <- thresholdImage(seg$segmentation, 1, Inf)
pseg <- priorBasedSegmentation(fi, seg$probabilityimages, msk, 0.25, 0.1, 3)