Package WhiteStripe details

White Matter Normalization for Magnetic Resonance Images using WhiteStripe

Shinohara (2014) introduced 'WhiteStripe', an intensity-based normalization of T1 and T2 images, where normal appearing white matter performs well, but requires segmentation. This method performs white matter mean and standard deviation estimates on data that has been rigidly-registered to the 'MNI' template and uses histogram-based methods.

Maintainer: John Muschelli < muschellij2 at gmail.com >

Documentation

From within R, enter citation('WhiteStripe')

Shinohara RT, Sweeney EM, Goldsmith J, Shiee N, Mateen FJ, Calabresi
PA, Jarso S, Pham DL, Reich DS, Crainiceanu CM, others (2014).
"Statistical normalization techniques for magnetic resonance imaging."
_NeuroImage: Clinical_, *6*, 9-19.

A BibTeX entry for LaTeX users is

@Article{shinohara2014statistical,
title = {Statistical normalization techniques for magnetic resonance imaging},
author = {Russell T Shinohara and Elizabeth M Sweeney and Jeff Goldsmith and Navid Shiee and Farrah J Mateen and Peter A Calabresi and Samson Jarso and Dzung L Pham and Daniel S Reich and Ciprian M Crainiceanu and {others}},
journal = {NeuroImage: Clinical},
volume = {6},
pages = {9--19},
year = {2014},
publisher = {Elsevier},
}

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('WhiteStripe')

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

More detailed installation instructions can be found here.