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) <doi:10.1016/j.csda.2014.12.001>. Latent labels are sampled using chequerboard updating or SwendsenWang. Algorithms for the smoothing parameter include pseudolikelihood, path sampling, the exchange algorithm, approximate Bayesian computation (ABCMCMC and ABCSMC), and the parametric functional approximate Bayesian (PFAB) algorithm. Refer to <doi:10.1007/9783030425531_6> for an overview and also to <doi:10.1007/s1122201495256> and <doi:10.1214/18BA1130> for further details of specific algorithms.
Package details 


Author  Matt Moores [aut, cre] (<https://orcid.org/0000000345313572>), Dai Feng [ctb], Kerrie Mengersen [aut, ths] (<https://orcid.org/0000000186259168>) 
Maintainer  Matt Moores <mmoores@gmail.com> 
License  GPL (>= 2)  file LICENSE 
Version  0.61 
URL  https://bitbucket.org/Azeari/bayesimages https://mooresm.github.io/bayesImageS/ 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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