Package oasis details

Multiple Sclerosis Lesion Segmentation using Magnetic Resonance Imaging (MRI)

Trains and makes predictions from the OASIS method, described in detail in the paper "OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI" . OASIS is a method for multiple sclerosis (MS) lesion segmentation on structural magnetic resonance image (MRI) studies. OASIS creates probability maps of lesion presence using the FLAIR, T2, T1, and PD structural MRI volumes. This packages allows for training of the OASIS model and prediction of OASIS probability maps from a trained model with user supplied studies that have a gold standard lesion segmentation masks. The package will also create OASIS probability maps for MRI studies using the OASIS model from the OASIS paper if no gold standard lesion segmentation masks are available.

Maintainer: Elizabeth M. Sweeney < elizabethmargaretsweeney at >


From within R, enter citation('oasis')


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

  Versions(Pending - no previous version)
To install this package, start R and enter:


# Default Install

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

More detailed installation instructions can be found here.


Initially submitted on October 3 2018 1:23PM
Last updated on March 31 2021 10:00AM
Package type standard
Source GitHub GitHub
Neuroconductor GitHub GitHub
DependsR (2.10)
Importsneurobase, fslr (2.13), methods, stats, parallel, oro.nifti, mmand
Suggestshttr, covr, ROCR