ANTsR (version 1.0)

aslDenoiseR: WIP: data-driven denoising for ASL MRI

Description

Denoises regression based reconstruction of CBF from arterial spin labeling

Usage

wmat<-aslDenoiseR( mat  )

Arguments

mat

input ASL matrix

Value

matrix is output

Examples

# NOT RUN {
asl<-antsImageRead("PEDS012_20131101_pcasl_1.nii.gz",4)
# image available at http://files.figshare.com/1701182/PEDS012_20131101.zip
tr<-antsGetSpacing(asl)[4]
aslmean<-getAverageOfTimeSeries( asl )
aslmask<-getMask(aslmean,lowThresh=mean(aslmean),cleanup=TRUE)
aslmat<-timeseries2matrix(asl,aslmask)
tc<-as.factor(rep(c("C","T"),nrow(aslmat)/2))
dv<-computeDVARS(aslmat)
dnz<-aslDenoiseR( aslmat, tc, motionparams=dv, selectionthresh=0.1,
  maxnoisepreds=c(2,4,6,8), debug=FALSE, polydegree=4,
  crossvalidationgroups=6 )
nzimg<-antsImageClone(aslmask)
nzimg[ aslmask == 1 ]<-dnz$R2final[,1]
antsImageWrite(nzimg,'nzimg1.nii.gz')
nzimg[ aslmask == 1 ]<-dnz$R2final[,2]
antsImageWrite(nzimg,'nzimg2.nii.gz')
# a classic regression approach to estimating perfusion
# not recommended, but shows the basic idea.
# see ?quantifyCBF for a better approach
perfmodel<-lm( aslmat ~ tc + dnz$noiseu + dv )
perfimg<-antsImageClone(aslmask)
perfimg[ aslmask == 1 ]<-bigLMStats( perfmodel )$beta.t[1,]
antsImageWrite(perfimg,'perf.nii.gz')
# }