ANTsR (version 1.0)

pairwiseImageDistanceMatrix: Simple pairwiseImageDistanceMatrix function for images

Description

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.

Usage

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

Examples

# NOT RUN {
  # dsimdata<-pairwiseImageDistanceMatrix( 3, imagefilelist, nclusters = 5 )
# }