| readIRData {qMRI} | R Documentation |
Prepare IRMRI dataset
Description
The function reads IRMRI images given as NIfTI files in t1Files, inversion times and segmentation image(s) aund prepares an object class "IRdata"
Usage
readIRData(t1Files, InvTimes, segmFile, sigma = NULL, L = 1,
segmCodes = c("GM", "WM", "CSF"))
Arguments
t1Files |
Names of NIfTI files containing the recorded images. |
InvTimes |
Corresponding inversion times |
segmFile |
Either a NIfTI file containing a segmentation into GM, WM and CSF or three files containing probability maps for GM, WM and CSF |
sigma |
Noise standard deviation |
L |
Effective number of coils, L=1 assumes a Rician signal distribution |
segmCodes |
sequence of tissue code in segmFile |
Value
A list of class "IRdata" with components
IRdata |
4D array containing the IRMRI data, first dimension refers to inversion times |
InvTimes |
vector of inversion times |
segm |
segmentation codes, 1 for CSF, 2 for GM, 3 for WM, 0 for out of brain |
sigma |
noise standard deviation, if not specified estimated fron CSF areas in image with largest inversion time |
L |
effective number of coils |
Author(s)
Karsten Tabelow tabelow@wias-berlin.de
J\"org Polzehl polzehl@wias-berlin.de
References
J. Polzehl and K. Tabelow (2023), Magnetic Resonance Brain Imaging: Modeling and Data Analysis Using R, 2nd Edition, Chapter 7, Springer, Use R! Series. <doi:10.1007/978-3-031-38949-8_7>.
J. Polzehl and K. Tabelow (2023), Magnetic Resonance Brain Imaging - Modeling and Data Analysis Using R: Code and Data. <doi:10.20347/WIAS.DATA.6>.
See Also
estimateIRfluid, estimateIRsolid, estimateIR,smoothIRSolid
Examples
dataDir0 <- system.file("extdataIR", package = "qMRI")
dataDir <- tempdir("IRdata")
library(oro.nifti)
library(qMRI)
segm <- readNIfTI(file.path(dataDir0,"Brainweb_segm"))
Sf <- 900
Rf <- 0.000285
Sgm <- 400
Rgm <- 0.00075
fgm <- .15
Swm <- 370
Rwm <- 0.0011
fwm <- .05
InvTimes0 <- c(100, 200, 400, 600, 800, 1200, 1600, 2000, 2500, 3000,
3500, 4000, 4500, 5000, 6000, 15000)
nTimes <- length(InvTimes0)
sigma <- 40
## generate IR signal
IRdata <- generateIRData(segm, c(Sf,Rf), c(fgm,Rgm,Sgm), c(fwm,Rwm,Swm), InvTimes0, sigma)
for(i in 1:9) writeNIfTI(as.nifti(IRdata[i,,,]),
file.path(dataDir,paste0("IR0",i)))
for(i in 10:nTimes) writeNIfTI(as.nifti(IRdata[i,,,]),
file.path(dataDir,paste0("IR",i)))
## generate IRdata object
t1Files <- list.files(dataDir,"*.nii.gz",full.names=TRUE)
segmFile <- file.path(dataDir0,"Brainweb_segm")
IRdata <- readIRData(t1Files, InvTimes0, segmFile, sigma=sigma,
L=1, segmCodes=c("CSF","GM","WM"))