Description Usage Arguments Value Author(s) Examples
Computes CBF from ASL - pasl or pcasl
1 | quantifyCBF(perfusion, mask, parameters, M0val = NA, outlierValue = 0.02)
|
perfusion |
input asl matrix |
mask |
3D image mask (antsImage) |
parameters |
list with entries for sequence and m0 (at minimimum) |
M0val |
baseline M0 value (optional) |
outlierValue |
trim outliers by this fractional value (optional) |
a list is output with 3 types of cbf images
Avants BB, Kandel B, Duda JT
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ## Not run:
if (!exists("fn") ) fn<-getANTsRData("pcasl")
# PEDS029_20101110_pcasl_1.nii.gz # high motion subject
asl<-antsImageRead(fn)
# image available at http://files.figshare.com/1701182/PEDS012_20131101.zip
pcasl.bayesian <- aslPerfusion( asl,
dorobust=0., useDenoiser=4, skip=11, useBayesian=1000,
moreaccurate=0, verbose=T, maskThresh=0.5 ) # throw away lots of data
# user might compare to useDenoiser=FALSE
pcasl.parameters <- list( sequence="pcasl", m0=pcasl.bayesian$m0 )
cbf <- quantifyCBF( pcasl.bayesian$perfusion, pcasl.bayesian$mask,
pcasl.parameters )
meancbf <- cbf$kmeancbf
print(mean(meancbf[ pcasl.bayesian$mask==1 ]))
antsImageWrite( meancbf , "temp.nii.gz")
pcasl.processing <- aslPerfusion( asl, moreaccurate=0,
dorobust=0.95, useDenoiser=NULL, skip=5, useBayesian=0 )
# user might compare to useDenoiser=FALSE
pcasl.parameters <- list( sequence="pcasl", m0=pcasl.processing$m0 )
cbf <- quantifyCBF( pcasl.processing$perfusion, pcasl.processing$mask, pcasl.parameters )
meancbf <- cbf$kmeancbf
print(mean(meancbf[ pcasl.processing$mask==1 ]))
antsImageWrite( meancbf , "temp2.nii.gz" )
plot( meancbf, slices="1x50x1" )
## End(Not run)
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