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qMRI (version 1.2.7.9)

extract-methods: 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 MPMData
extract(x, what, ...)
# S3 method for ESTATICSModel
extract(x, what, ...)
# S3 method for sESTATICSModel
extract(x, what, ...)
# S3 method for qMaps
extract(x, what, ...)
# S3 method for IRdata
extract(x, what, ...)
# S3 method for IRfluid
extract(x, what, ...)
# S3 method for IRmixed
extract(x, what, ...)
# S3 method for MPMData
[(x, i, j, k, ...)
# S3 method for ESTATICSModel
[(x, i, j, k, ...)
# S3 method for sESTATICSModel
[(x, i, j, k, ...)
# S3 method for qMaps
[(x, i, j, k, ...)
# S3 method for IRdata
[(x, i, j, k, tind, ...)
# S3 method for IRfluid
[(x, i, j, k, ...)
# S3 method for IRmixed
[(x, i, j, k, ...)

Value

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

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.

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

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>.