Simple pairwiseImageDistanceMatrix function for images — pairwiseImageDistanceMatrix • ANTsR

Output contains the NImages x NImages matrix of c('PearsonCorrelation','Mattes') or any Image Metric values available in iMath. Similarity is computed after an affine registration is performed. You can also cluster the images via the dissimilarity measurement, i.e. the negated similarity metric. So, the estimated dissimilarity is returned in the matrix.

pairwiseImageDistanceMatrix(
  dim,
  myFileList,
  metrictype = "PearsonCorrelation",
  nclusters = NA
)

Arguments

dim: imageDimension
myFileList: dd<-'MICCAI-2013-SATA-Challenge-Data/CAP/training-images/' myFileList<-list.files(path=dd, pattern = glob2rx('*nii.gz'),full.names = T,recursive = T)
metrictype: similarity function
nclusters: integer controlling max number of clusters to search over

Value

raw dissimilarity matrix is output, symmetrized matrix and clustering (optional) in a list

Author

Avants BB

Examples

if (FALSE) { # \dontrun{
# dsimdata<-pairwiseImageDistanceMatrix( 3, imagefilelist, nclusters = 5 )
} # }