Novel Bayesian multiscale method for speckle removal in medical ultrasound images

Alin Achim, Anastasios Bezerianos, Panagiotis Tsakalides

Research output: Contribution to journalArticle

Abstract

A novel speckle suppression method for medical ultrasound images is presented. First, the logarithmic transform of the original image is analyzed into the multiscale wavelet domain. We show that the subband decompositions of ultrasound-images have significantly non-Gaussian statistics that are best described by families of heavy-tailed distributions such as the alpha-stable. Then, we design a Bayesian estimator that exploits these statistics. We use the alpha-stable model to develop a blind noise-removal processor that performs a nonlinear operation on the data. Finally, we compare our technique with current state-of-the-art soft and hard thresholding methods applied on actual ultrasound medical images and we quantify the achieved performance improvement.

Original languageEnglish (US)
Pages (from-to)772-783
Number of pages12
JournalIEEE transactions on medical imaging
Volume20
Issue number8
DOIs
StatePublished - Aug 1 2001

Keywords

  • Alpha-stable distributions
  • Bayesian estimation
  • Ultrasound speckle
  • Wavelet decomposition

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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