Package dcemriS4 details

A Package for Image Analysis of DCE-MRI (S4 Implementation)

A collection of routines and documentation that allows one to perform voxel-wise quantitative analysis of dynamic contrast-enhanced MRI (DEC-MRI) and diffusion-weighted imaging (DWI) data, with emphasis on oncology applications.

Maintainer: Brandon Whitcher < bwhitcher at gmail.com >

 
From within R, enter citation(dcemriS4)


To cite dcemriS4 in publications use:

Brandon Whitcher, Volker J. Schmid (2011). Quantitative Analysis of
Dynamic Contrast-Enhanced and Diffusion-Weighted Magnetic Resonance
Imaging for Oncology in R. Journal of Statistical Software, 44(5),
1-29. URL http://www.jstatsoft.org/v44/i05/.

A BibTeX entry for LaTeX users is

@Article{,
title = {Quantitative Analysis of Dynamic Contrast-Enhanced and Diffusion-Weighted Magnetic Resonance Imaging for Oncology in {R}},
author = {Brandon Whitcher and Volker J. Schmid},
journal = {Journal of Statistical Software},
year = {2011},
volume = {44},
number = {5},
pages = {1--29},
url = {http://www.jstatsoft.org/v44/i05/},
}

 

If you have any problems with this package you can open a new issue or check the already existing ones here.

 
 
To install this package, start R and enter:

source("https://neuroconductor.org/neurocLite.R")

# Default Install
neuro_install('dcemriS4')

# From the Binary Repo in NeuroC
neuro_install('dcemriS4', release = "stable", release_repo = binary_release_repo(release = "stable"))
neuro_install('dcemriS4', release = "current", release_repo = binary_release_repo(release = "current"))

# from GitHub
neuro_install('dcemriS4', release = "stable", release_repo = "github")
neuro_install('dcemriS4', release = "current", release_repo = "github")

More detailed installation instructions can be found here.

 

Initially submitted on September 30 2018 12:49PM
Last updated on July 28 2019 12:01AM
Package type standard
Source GitHub https://github.com/bjw34032/dcemriS4 GitHub
Neuroconductor GitHub https://github.com/neuroconductor/dcemriS4 GitHub
DependsR (2.14.0), minpack.lm, oro.nifti (0.5.0)
Importsutils, parallel, methods
Suggestsbitops, splines, XML, oro.dicom (0.5.0), testthat