extract-methods {qMRI}

Methods to extract information from objects of class "MPMData", "ESTATICSModel", "sESTATICSModel", "qMaps", "IRdata", "IRfluid" and "IRmixed".

Description

The extract-methods extract and/or compute specified statistics from object of class "MPMData", "ESTATICSModel", "sESTATICSModel", "qMaps", "IRdata", "IRfluid" and "IRmixed". The [-methods can be used to reduce objects of class "MPMData", "ESTATICSModel", "sESTATICSModel", "qMaps", "IRdata", "IRfluid" and "IRmixed" such that they contain a subcube of data and results.

Usage

## S3 method for class 'MPMData'
extract(x, what, ...)
## S3 method for class 'ESTATICSModel'
extract(x, what, ...)
## S3 method for class 'sESTATICSModel'
extract(x, what, ...)
## S3 method for class 'qMaps'
extract(x, what, ...)
## S3 method for class 'IRdata'
extract(x, what, ...)
## S3 method for class 'IRfluid'
extract(x, what, ...)
## S3 method for class 'IRmixed'
extract(x, what, ...)
## S3 method for class 'MPMData'
x[i, j, k, ...]
## S3 method for class 'ESTATICSModel'
x[i, j, k, ...]
## S3 method for class 'sESTATICSModel'
x[i, j, k, ...]
## S3 method for class 'qMaps'
x[i, j, k, ...]
## S3 method for class 'IRdata'
x[i, j, k, tind, ...]
## S3 method for class 'IRfluid'
x[i, j, k, ...]
## S3 method for class 'IRmixed'
x[i, j, k, ...]

Arguments

x

object of class "MPMData", "ESTATICSModel", "sESTATICSModel" or "qMaps".

what

Character vector of of names of statistics to extract. See Methods Section for details.

i

index vector for first spatial dimension

j

index vector for second spatial dimension

k

index vector for third spatial dimension

tind

index vector for inversion times

...

additional parameters, currently unused.

Value

A list with components carrying the names of the options specified in argument what.

Methods

class(x) = "ANY"

Returns a warning for extract

class(x) = "MPMData"

Depending the occurence of names in what a list with the specified components is returned

• ddata: mpm data

• sdim: dimension of image cube

• nFiles: number of images / image files

• t1Files: character - filenames of t1Files

• pdFiles: character - filenames of pdFiles

• mtFiles: character - filenames of mtFiles

• model: Number of the ESTATICS model that can be used

• maskFile: character - filenames of maskFile

• mask: mask

• TR: vector of TR values

• TE: vector of TE values

• FA: vector of FA values

class(x) = "ESTATICSModel"

Depending the occurence of names in what a list with the specified components is returned

• modelCoeff: Estimated parameter maps

• invCov: map of inverse covariance matrices

• rsigma: map of residual standard deviations

• isConv: convergence indicator map

• isThresh: logical map indicating where R2star==maxR2star

• sdim: image dimension

• nFiles: number of images

• t1Files: vector of T1 filenames

• pdFiles: vector of PD filenames

• mtFiles: vector of MT filenames

• model: model used (depends on specification of MT files)

• maskFile: filename of brain mask

• mask: brain mask

• sigma: standard deviation sigma

• L: effective number of receiver coils L

• TR: TR values

• TE: TE values

• FA: Flip angles (FA)

• TEScale: TEScale

• dataScale: dataScale

class(x) = "sESTATICSModel"

Depending the occurence of names in what a list with the specified components is returned

• modelCoeff: Estimated parameter maps

• invCov: map of inverse covariance matrices

• rsigma: map of residual standard deviations

• isConv: convergence indicator map

• bi: Sum of weights map from AWS/PAWS

• smoothPar: smooting parameters used in AWS/PAWS

• smoothedData: smoothed mpmData

• isThresh: logical map indicating where R2star==maxR2star

• sdim: image dimension

• nFiles: number of images

• t1Files: vector of T1 filenames

• pdFiles: vector of PD filenames

• mtFiles: vector of MT filenames

• model: model used (depends on specification of MT files)

• maskFile: filename of brain mask

• mask: brain mask

• sigma: sigma

• L: effective number of receiver coils L

• TR: TR values

• TE: TE values

• FA: Flip angles (FA)

• TEScale: TEScale

• dataScale: dataScale

class(x) = "qMaps"

Depending the occurence of names in what a list with the specified components is returned

• b1Map: b1Map

• R1: Estimated map of R1

• R2star: Estimated map of R2star

• PD: Estimated map of PD

• MT: Estimated map of delta (if MT-series was used)

• model: Type of ESTATICS model used

• t1Files: filenames T1

• mtFiles: filenames MT

• pdFiles: filenames PD

• mask: brainmask

Author(s)

Karsten Tabelow [e-mail]
J\"org Polzehl [e-mail]

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>.