Package: oasis
Type: Package
Title: Multiple Sclerosis Lesion Segmentation using Magnetic Resonance
        Imaging (MRI)
Version: 3.0.4
Date: 2018-02-20
Authors@R: c(person(given = "Elizabeth M.", "Sweeney",  
  email = "elizabethmargaretsweeney@gmail.com", role = c("aut", "cre")), 
  person(given = "John", family = "Muschelli", email = "muschellij2@gmail.com", 
  role = c("aut")), 
  person(  given = "R. Taki", family = "Shinohara", 
  email = "rshi@mail.med.upenn.edu", 
  role = c("aut")))
Description: 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" 
    <doi:10.1016/j.nicl.2013.03.002>. 
    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.
Depends: R (>= 2.10)
Imports: neurobase, fslr (>= 2.13), methods, stats, parallel,
        oro.nifti, mmand
Suggests: httr, covr, ROCR
License: GPL-2
LazyLoad: yes
LazyData: yes
Encoding: UTF-8
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-02-21 02:58:51 UTC; johnmuschelli
Author: Elizabeth M. Sweeney [aut, cre],
  John Muschelli [aut],
  R. Taki Shinohara [aut]
Maintainer: Elizabeth M. Sweeney <elizabethmargaretsweeney@gmail.com>
Repository: CRAN
Date/Publication: 2018-02-21 18:22:15 UTC
