bayesImageS (0.6-0)

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Bayesian Methods for Image Segmentation using a Potts Model.

Various algorithms for segmentation of 2D and 3D images, such as computed tomography and satellite remote sensing. This package implements Bayesian image analysis using the hidden Potts model with external field prior of Moores et al. (2015) . Latent labels are sampled using chequerboard updating or Swendsen-Wang. Algorithms for the smoothing parameter include pseudolikelihood, path sampling, the exchange algorithm, approximate Bayesian computation (ABC-MCMC and ABC-SMC), and the parametric functional approximate Bayesian (PFAB) algorithm. Refer to and for further details.

Maintainer: Matt Moores
Author(s): Matt Moores [aut, cre] (<>), Kerrie Mengersen [aut, ths] (<>), Dai Feng [ctb]

License: GPL (>= 2) | file LICENSE

Uses: Rcpp, coda, lattice, PottsUtils, knitr, mcmcse, rmarkdown, rstan

Released about 1 year ago.

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