# tools:::Rd_package_title("qMRI") tools:::Rd_package_description("qMRI") package ## Details The DESCRIPTION file: tools:::Rd_package_DESCRIPTION("qMRI") tools:::Rd_package_indices("qMRI") ## Author(s) Karsten Tabelow tabelow@wias-berlin.de J\"org Polzehl polzehl@wias-berlin.de Maintainer: tools:::Rd_package_maintainer("qMRI") ## References Weiskopf, N.; Suckling, J.; Williams, G.; Correia, M. M.; Inkster, B.; Tait, R.; Ooi, C.; Bullmore, E. T. & Lutti, A. Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation. Front Neurosci, Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, UK., 2013, 7, 95 J. Polzehl and K. Tabelow (2023), Magnetic Resonance Brain Imaging: Modeling and Data Analysis Using R, 2nd Edition, Chapter 6 and 7, Springer, Use R! Series. . J. Polzehl and K. Tabelow (2023), Magnetic Resonance Brain Imaging - Modeling and Data Analysis Using R: Code and Data. . ## Examples ```r dataDir <- system.file("extdata",package="qMRI") # # set file names for T1w, MTw and PDw images # t1Names <- paste0("t1w_",1:8,".nii.gz") mtNames <- paste0("mtw_",1:6,".nii.gz") pdNames <- paste0("pdw_",1:8,".nii.gz") t1Files <- file.path(dataDir, t1Names) mtFiles <- file.path(dataDir, mtNames) pdFiles <- file.path(dataDir, pdNames) # # file names of mask and B1 field map # B1File <- file.path(dataDir, "B1map.nii.gz") maskFile <- file.path(dataDir, "mask.nii.gz") # # Acquisition parameters (TE, TR, Flip Angle) for T1w, MTw and PDw images # TE <- c(2.3, 4.6, 6.9, 9.2, 11.5, 13.8, 16.1, 18.4, 2.3, 4.6, 6.9, 9.2, 11.5, 13.8, 2.3, 4.6, 6.9, 9.2, 11.5, 13.8, 16.1, 18.4) TR <- rep(25, 22) FA <- c(rep(21, 8), rep(6, 6), rep(6, 8)) # # read MPM example data # library(qMRI) mpm <- readMPMData(t1Files, pdFiles, mtFiles, maskFile, TR = TR, TE = TE, FA = FA, verbose = FALSE) # # Estimate Parameters in the ESTATICS model # modelMPM <- estimateESTATICS(mpm, method = "NLR") # # smooth maps of ESTATICS Parameters # setCores(2) modelMPMsp1 <- smoothESTATICS(modelMPM, kstar = 16, alpha = 0.004, patchsize=1, verbose = TRUE) # # resulting ESTATICS parameter maps for central coronal slice # if(require(adimpro)){ rimage.options(zquantiles=c(.01,.99), ylab="z") oldpar <- par(mfrow=c(2,4),mar=c(3,3,3,1),mgp=c(2,1,0)) on.exit(par(oldpar)) pnames <- c("T1","MT","PD","R2star") modelCoeff <- extract(modelMPM,"modelCoeff") for(i in 1:4){ rimage(modelCoeff[i,,11,]) title(pnames[i]) } modelCoeff <- extract(modelMPMsp1,"modelCoeff") for(i in 1:4){ rimage(modelCoeff[i,,11,]) title(paste("smoothed",pnames[i])) } } # # Compute quantitative maps (R1, R2star, PD, MT) # qMRIMaps <- calculateQI(modelMPM, b1File = B1File, TR2 = 3.4) qMRISmoothedp1Maps <- calculateQI(modelMPMsp1, b1File = B1File, TR2 = 3.4) # # resulting quantitative maps for central coronal slice # if(require(adimpro)){ rimage.options(zquantiles=c(.01,.99), ylab="z") par(mfrow=c(2,4),mar=c(3,3,3,1),mgp=c(2,1,0)) nmaps <- c("R1","R2star","PD","MT") qmap <- extract(qMRIMaps,nmaps) for (i in 1:4) rimage(qmap[[i]][,11,],main=nmaps[i]) qmap <- extract(qMRISmoothedp1Maps,nmaps) for (i in 1:4) rimage(qmap[[i]][,11,],main=paste("Smoothed",nmaps[i])) } par(oldpar) ``` ## See Also `aws`

qMRI-package