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

Oddvar Husby; Torgrim Lio; Thomas Lang; Jrn Hokland; Hävard Rue

doi:10.1109/58.895918

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

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

Research output: Contribution to journal › Article › peer-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 language	English (US)
Pages (from-to)	121-130
Number of pages	10
Journal	IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Volume	48
Issue number	1
DOIs	https://doi.org/10.1109/58.895918
State	Published - Jan 2001
Externally published	Yes

ASJC Scopus subject areas

Instrumentation
Acoustics and Ultrasonics
Electrical and Electronic Engineering

Access to Document

10.1109/58.895918

Cite this

@article{ef2c39d6c429466f978e34fbb40901ba,

title = "Bayesian 2-D deconvolution: A model for diffuse ultrasound scattering",

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.",

author = "Oddvar Husby and Torgrim Lio and Thomas Lang and Jrn Hokland and H{\"a}vard Rue",

year = "2001",

month = jan,

doi = "10.1109/58.895918",

language = "English (US)",

volume = "48",

pages = "121--130",

journal = "IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control",

issn = "0885-3010",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "1",

}

TY - JOUR

T1 - Bayesian 2-D deconvolution

T2 - A model for diffuse ultrasound scattering

AU - Husby, Oddvar

AU - Lio, Torgrim

AU - Lang, Thomas

AU - Hokland, Jrn

AU - Rue, Hävard

PY - 2001/1

Y1 - 2001/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0034745853&partnerID=8YFLogxK

U2 - 10.1109/58.895918

DO - 10.1109/58.895918

M3 - Article

C2 - 11367779

AN - SCOPUS:0034745853

SN - 0885-3010

VL - 48

SP - 121

EP - 130

JO - IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

JF - IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

IS - 1

ER -

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

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this