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Statistical models for speckle noise and Bayesian deconvolution of ultrasound images

Statistical models for speckle noise and Bayesian deconvolution of ultrasound images

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This chapter first summarizes existing results related to the statistical properties of US images based on both radio-frequency (RF) and envelope signals. In a second part of the chapter, we present a Bayesian deconvolution method that can be viewed as a general despeckling technique.

Chapter Contents:

  • 3.1 Statistical analysis of speckle noise
  • 3.1.1 Statistical models for radio-frequency signals
  • 3.1.1.1 Gaussian distribution
  • 3.1.1.2 K RF distribution
  • 3.1.1.3 Generalized Gaussian distribution
  • 3.1.1.4 α-Stable distributions
  • 3.1.2 Statistical models for envelope signals
  • 3.1.2.1 Rayleigh distribution
  • 3.1.2.2 Rice distribution
  • 3.1.2.3 K distribution
  • 3.1.2.4 Homodyned-K distribution
  • 3.1.2.5 Nakagami distribution
  • 3.1.2.6 α-Rayleigh distribution
  • 3.1.3 Statistical models for B-mode image
  • 3.1.4 Brief review of statistical despeckling techniques
  • 3.1.4.1 Image filtering
  • 3.1.4.2 Compounding
  • 3.2 Bayesian method for US image deconvolution
  • 3.2.1 Bayesian model for joint deconvolution and segmentation
  • 3.2.1.1 Likelihood
  • 3.2.1.2 Prior distributions
  • 3.2.1.3 Joint posterior distribution
  • 3.2.2 Sampling the posterior and computing Bayesian estimators
  • 3.2.2.1 Hybrid Gibbs sampler
  • 3.2.2.2 Parameter estimation
  • 3.2.3 Experimental results
  • 3.3 Conclusions
  • References

Inspec keywords: Bayes methods; medical image processing; deconvolution; biomedical ultrasonics; statistical analysis; image denoising

Other keywords: speckle noise; ultrasound images; radiofrequency signals; despeckling technique; envelope signals; statistical models; Bayesian deconvolution

Subjects: Probability theory, stochastic processes, and statistics; Computer vision and image processing techniques; Optical, image and video signal processing; Other topics in statistics; Patient diagnostic methods and instrumentation; Other topics in statistics; Biology and medical computing; Sonic and ultrasonic radiation (medical uses); Sonic and ultrasonic radiation (biomedical imaging/measurement); Sonic and ultrasonic applications

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