BayesBD: An R Package for Bayesian Inference on Image Boundaries

We present the \pkg{BayesBD} package providing Bayesian inference for boundaries of noisy images. The \pkg{BayesBD} package implements flexible Gaussian process priors indexed by the circle to recover the boundary in a binary or Gaussian noised image, and achieves four aims of guaranteed geometric restriction, (nearly) minimax optimal rate adaptive to the smoothness level, convenience for joint inference, and computational efficiency. The core sampling tasks are carried out in \code{c++} using packages \pkg{Rcpp} and \pkg{RcppArmadillo}. Users can access the full functionality of the package in both \code{Rgui} and the corresponding \pkg{shiny} application. We demonstrate the usage of \pkg{BayesBD} both in simulations and a real data application in brain oncology.