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 >


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

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:


# Default Install

# 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.


Initially submitted on October 1 2018 10:19AM
Last updated on October 15 2020 2:50PM
Package type standard
Source GitHub GitHub
Neuroconductor GitHub GitHub
Reverse Importssmri.process, mimosa (2.3.1), extrantsr, RAVEL