The mimosa package trains and makes predictions from the MIMoSA
method. Access to the full papers can be found
here and
here. Additionally, it
allows for implementation of some common segmentation metrics such as
true positive rate, false positive rate, false negative rate, false
positive count, and sensitivity based on lesion count.
To install the package from Neuroconductor, type:
source("https://neuroconductor.org/neurocLite.R")
neuro_install("mimosa")To get the latest development version from GitHub:
devtools::install_github('avalcarcel9/mimosa')avalcarcel9 badges:
muschellij2 badges:
Check out our pkgdown site
here.
Full functions and documentation references are available here.
For a full implementation of the methods with output please see our vignette.