An external field prior for the hidden Potts model, with application to cone-beam computed tomography

By Moores Matt, Hargrave Catriona, Deegan Timothy, Poulsen Michael, Harden Fiona, and Mengersen Kerrie
Computational Statistics and Data Analysis (2015)

  • Matt Moores

    University of Warwick

    UK

  • Kerrie Mengersen

Created

March 24, 2014

Last update

July 24, 2014

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Description

R package 'bayesImageS' implements algorithms for segmentation of 2D and 3D images, such as computed tomography (CT) and satellite remote sensing. It provides functions for Bayesian image analysis using the hidden Potts/Ising model with external field prior. Latent labels are updated using chequerboard Gibbs sampling or Swendsen-Wang. Algorithms for the smoothing parameter include: pseudolikelihood; path sampling (thermodynamic integration); the exchange algorithm; approximate Bayesian computation (ABC-MCMC and ABC-SMC); and Bayesian indirect likelihood (BIL).

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