aslPerfusion: ASL-based Perfusion from PASL, CASL or pCASL.

In stnava/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

ASL-based Perfusion from PASL, CASL or pCASL.

Description

This function will estimate perfusion from an ASL time series using a (robust) regression approach. It will do motion correction, compcorr, factor out nuisance variables and use regression to estimate the perfusion itself. It will mask the image too based on a simple procedure ( should fix this in the future by allowing the user to optionally pass a mask in from the outside ). WARNING: the function will estimate the m0 image from the mean of the control tags assuming that the data is acquired T C T C as is most of JJ's data. Quantitative CBF can be obtained by mutiplying the output of this function by a scalar.

Usage

aslPerfusion(
  asl,
  maskThresh = 0.75,
  moreaccurate = 1,
  dorobust = 0.92,
  m0 = NA,
  skip = 20,
  mask = NULL,
  checkmeansignal = 100,
  moco_results = NULL,
  regweights = NULL,
  useDenoiser = NULL,
  useBayesian = 0,
  verbose = FALSE,
  ncompcor = 0,
  N3 = FALSE
)

Arguments

asl	input asl image
maskThresh	for estimating a brain mask
moreaccurate	zero, one or two with the last being the most accurate
dorobust	robustness parameter, lower value keeps more data
m0	known M0 if any
skip	stride to speed up robust regression weight estimates
mask	known brain mask
checkmeansignal	throw out volumes with mean lower than this thresh
moco_results	passes prior motion results so moco does not get repeated
regweights	known temporal weights on regression solution, if any
useDenoiser	use the aslDenoiser if this value is a range gt than zero
useBayesian	strength of bayesian prior
verbose	bool
ncompcor	number of compcor parameters
N3	bool correct target image before motion corr

Value

output a list of relevant objects

Author(s)

Avants BB

Examples

# image available at http://files.figshare.com/1701182/PEDS012_20131101.zip
# fn<-'PEDS012_20131101_pcasl_1.nii.gz'
# asl<-antsImageRead(fn,4)
set.seed(1)
nvox <- 5 * 5 * 5 * 10
dims <- c(5, 5, 5, 10)
asl <- makeImage(dims, rnorm(nvox) + 500) %>% iMath("PadImage", 2)
aslmean <- getAverageOfTimeSeries(asl)
aslmask <- getMask(aslmean, 0.001, Inf)
aslmat <- timeseries2matrix(asl, aslmask)
for (i in 1:10) aslmat[, i * 2] <- aslmat[, i * 2] * 2
asl <- matrix2timeseries(asl, aslmask, aslmat)
# NOT WORKING
## Not run: 
pcasl.processing <- aslPerfusion(asl, moreaccurate = 1, dorobust = 0)
testthat::expect_equal(mean(pcasl.processing$m1), 62.2115522470984)
pcasl.processing <- aslPerfusion(asl, moreaccurate = 1, ncompcor = 2)
# allow some rejection
pcasl.processing <- aslPerfusion(asl, moreaccurate = 1, dorobust = 0.925)

## End(Not run)

stnava/ANTsR documentation built on April 16, 2024, 12:17 a.m.