Title :
Bayesian 2-D deconvolution: a model for diffuse ultrasound scattering
Author :
Husby, Oddvar ; Lie, Torgrinn ; Langø, Thomas ; Hokland, Jørn ; Rue, Håvard
Author_Institution :
Dept. of Math. Sci, NTNU, Trondheim, Norway
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.
Keywords :
Bayes methods; Markov processes; Monte Carlo methods; biomedical ultrasonics; deconvolution; image enhancement; image restoration; medical image processing; modelling; speckle; statistical analysis; ultrasonic scattering; 2D ultrasound RF images; Bayesian 2D deconvolution; Markov chain Monte Carlo method; acoustic tissue reflectance; blur removal; diffuse US scattering model; diffuse ultrasound scattering; image restoration; medical ultrasound images; physical model; spatial smoothness constraints; speckle removal; statistical model; Acoustic scattering; Bayesian methods; Biomedical imaging; Deconvolution; Degradation; Image restoration; Medical diagnostic imaging; Radio frequency; Speckle; Ultrasonic imaging; Algorithms; Bayes Theorem; Computer Simulation; Image Processing, Computer-Assisted; Markov Chains; Models, Statistical; Monte Carlo Method; Scattering, Radiation; Ultrasonography;
Journal_Title :
Ultrasonics, Ferroelectrics, and Frequency Control, IEEE Transactions on
