Title: Multiple Sclerosis Lesion Segmentation using Magnetic Resonance
Authors@R: c(person(given = "Elizabeth M.", "Sweeney",
email = "emsweene@jhsph.edu", role = c("aut", "cre")),
person(given = "John", family = "Muschelli", email = "muschellij2@gmail.com",
person(  given = "R. Taki", family = "Shinohara",
Maintainer: Elizabeth M. Sweeney <emsweene@jhsph.edu>
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"
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
Packaged: 2015-12-26 18:11:17 UTC; johnmuschelli
Author: Elizabeth M. Sweeney [aut, cre],

Package: oasis
Type: Package
Title: Multiple Sclerosis Lesion Segmentation using Magnetic Resonance
Imaging (MRI)
Version: 2.1
Date: 2016-09-23
Authors@R: c(person(given = "Elizabeth M.", "Sweeney",
email = "emsweene@jhsph.edu", 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")))
Maintainer: Elizabeth M. Sweeney <emsweene@jhsph.edu>
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.
Imports: neurobase, fslr (>= 2.0), methods, stats, parallel, oro.nifti,
mmand
Suggests: httr
License: GPL-2
LazyLoad: yes
LazyData: yes
RoxygenNote: 5.0.1.9000
NeedsCompilation: no
Packaged: 2016-09-29 00:53:10 UTC; johnmuschelli
Author: Elizabeth M. Sweeney [aut, cre],
John Muschelli [aut],
R. Taki Shinohara [aut]
Repository: CRAN
Date/Publication: 2016-09-29 23:58:02