Cart (Loading....) | Create Account
Close category search window
 

Bayesian speckle tracking. Part II: biased ultrasound displacement estimation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Byram, B. ; Dept. of Biomed. Eng., Duke Univ., Durham, NC, USA ; Trahey, G.E. ; Palmeri, M.

Ultrasonic displacement estimates have numerous clinical uses, including blood flow estimation, elastography, therapeutic guidance, and acoustic radiation force imaging (ARFI). These clinical tasks could be improved with better ultrasonic displacement estimates. Traditional ultrasonic displacement estimates are limited by the Cramer-Rao lower bound (CRLB). The CRLB can be surpassed using biased estimates. In this paper, a framework for biased estimation using Bayes' theorem is described. The Bayesian displacement estimation method is tested against simulations of several common types of motion: bulk, step, compression, and acoustic-radiation-force-induced motion. Bayesian estimation is also applied to in vivo ARFI of cardiac ablation lesions. The Bayesian estimators are compared with the unbiased estimator, normalized cross-correlation. As an example, the peak displacement of the simulated acoustic radiation force response is reported because this position results in the noisiest estimates. Estimates were made with a 1.5-λ kernel and 20 dB SNR on 100 data realizations. Estimates using normalized cross-correlation and the Bayes' estimator had mean-square errors of 17 and 7.6 μm2, respectively, and contextualized by the true displacement magnitude, 10.9 μm. Biases for normalized cross-correlation and the Bayes' estimator are -0.12 and -0.28 μm, respectively. In vivo results show qualitative improvements. The results show that with small amounts of additional information, significantly improved performance can be realized.

Published in:

Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on  (Volume:60 ,  Issue: 1 )

Date of Publication:

January 2013

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.