The goal of rtapas is to determine a subject-specific threshold to
apply to multiple sclerosis lesion probability maps for automatic
segmentation. This R package is based on the Thresholding Approach for
Probability Map Automatic Segmentation (TAPAS) method. The methods are
in progress for publication. This package creates data structures
necessary for training the TAPAS model. After training, the model can be
used to predict subject-specific thresholds to use on probability maps
for automatic lesion segmentation. Methods can be extended outside of
multiple sclerosis lesion segmentation but have not been validated.
To install the package from Neuroconductor, type:
source("https://neuroconductor.org/neurocLite.R")
neuro_install("rtapas")To get the latest development version from GitHub:
# install.packages('remotes')
library(remotes)
remotes::install_github('avalcarcel9/rtapas')This package is documented using pkgdown. You can find the general
rtapas pkgdown site here
and the tutorial/vignette
here.
The GitHub tutorial/vignette is available
here.