oasis: 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" <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.

Getting started

Package details

AuthorElizabeth M. Sweeney [aut, cre], John Muschelli [aut], R. Taki Shinohara [aut]
MaintainerElizabeth M. Sweeney <elizabethmargaretsweeney@gmail.com>
Package repositoryView on CRAN
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oasis documentation built on May 2, 2019, 2:31 a.m.