By Topic

Parametric estimation of 2-D motion field on ultrasonic images using spatially smoothed regression model and respiration

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

5 Author(s)
Tagawa, N. ; Dept. of Electr. Eng., Tokyo Metropolitan Univ., Japan ; Ohta, K. ; Minagawa, A. ; Moriya, T.
more authors

An extension of a previously presented algorithm for estimating instantaneous 2-D motion fields in the ultrasonography of internal organs is proposed. In the previous algorithm, the motion field was modeled as a regression random process with respect to the respiratory signal, and utilized spatially independent unknown coefficients. However, the value of these coefficients should vary with spatial smoothness, which enables a spatial constraint to be applied. In the proposed extension, the regression coefficients are defined as random variables, i.e. Gaussian-Markov random field (GMRF), with unknown scale factors, allowing a computationally stable estimation algorithm to be constructed

Published in:

Ultrasonics Symposium, 2000 IEEE  (Volume:2 )

Date of Conference:

Oct 2000