ANTsR (version 0.3.3)

clusterTimeSeries: Split time series image into k distinct images

Description

Uses clustering methods to split a time series into similar subsets.

Usage

clusterTimeSeries(mat, krange = 2:10, nsvddims = NA, criterion = "asw")

Arguments

mat

input time series matrix

krange

k cluster range to explore

nsvddims

eg 2

criterion

for clustering see pamk

Value

matrix is output

Examples

## Not run: 
#   if (!exists("fn") ) fn<-getANTsRData("pcasl")
#    # high motion subject
#   asl<-antsImageRead(fn,4)
#   tr<-antsGetSpacing(asl)[4]
#   aslmean<-getAverageOfTimeSeries( asl )
#   aslmask<-getMask(aslmean,lowThresh=mean(aslmean),cleanup=TRUE)
#   omat<-timeseries2matrix(asl, aslmask )
#   clustasl<-clusterTimeSeries( omat, krange=4:10 )
#   for ( ct in 1:max(clustasl$clusters) )
#     {
#     sel<-clustasl$clusters != ct
#     img<-matrix2timeseries( asl, aslmask, omat[sel,] )
#     perf <- aslPerfusion( img, 
#       dorobust=0.9, useDenoiser=4, skip=10, useBayesian=0,
#       moreaccurate=0, verbose=F, mask=aslmask )
#     perfp <- list( sequence="pcasl", m0=perf$m0 )
#     cbf <- quantifyCBF( perf$perfusion, perf$mask, perfp )
#     }
#   ## End(Not run)