Segmentation of ultrasound images using a spatially coherent generalized Rayleigh mixture model

Marcelo A. Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
Original languageEnglish
Title of host publication2011 19th European Signal Processing Conference
Pages664-668
Number of pages5
Publication statusPublished - 2011

Keywords

  • Markov processes
  • Monte Carlo methods
  • belief networks
  • biological tissues
  • biomedical ultrasonics
  • image segmentation
  • medical image processing
  • Markov chain Monte Carlo method
  • heavy-tailed Rayleigh distributions
  • hybrid Metropolis-within-Gibbs sampler
  • label vector
  • multiple-tissue high-frequency ultrasound image segmentation
  • original Bayesian algorithm
  • spatially coherent generalized Rayleigh mixture model
  • statistical distribution
  • Bayes methods
  • Image segmentation
  • Lesions
  • Skin
  • Three-dimensional displays
  • Ultrasonic imaging
  • Bayesian estimation
  • Gibbs sampler
  • Heavy-tailed Rayleigh distribution
  • Potts-Markov field
  • mixture model

Cite this

Pereyra, M. A., Dobigeon, N., Batatia, H., & Tourneret, J-Y. (2011). Segmentation of ultrasound images using a spatially coherent generalized Rayleigh mixture model. In 2011 19th European Signal Processing Conference (pp. 664-668)