Bayesian 2-D deconvolution: A model for diffuse ultrasound scattering

Oddvar Husby, Torgrim Lio, Thomas Lang, Jrn Hokland, Haavard Rue

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Observed medical ultrasound images are degraded representations of the true acoustic tissue reflectance. The degradation is due to blur and speckle and significantly reduces the diagnostic value of the images. To remove both blur and speckle, we have developed a new statistical model for diffuse scattering in 2-D ultrasound radio frequency images, incorporating both spatial smoothness constraints and a physical model for diffuse scattering. The modeling approach is Bayesian in nature, and we use Markov chain Monte Carlo methods to obtain the restorations. The results from restorations of some real and simulated radio frequency ultrasound images are presented and compared with results produced by Wiener filtering.

Original languageEnglish (US)
Pages (from-to)121-130
Number of pages10
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Volume48
Issue number1
DOIs
StatePublished - Jan 1 2001

ASJC Scopus subject areas

  • Instrumentation
  • Acoustics and Ultrasonics
  • Electrical and Electronic Engineering

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