DocumentCode :
1745073
Title :
Parametric estimation of 2-D motion field on ultrasonic images using spatially smoothed regression model and respiration
Author :
Tagawa, Norio ; Ohta, Kazushi ; Minagawa, Akihiro ; Moriya, Tadashi ; Minohara, Shinichi
Author_Institution :
Dept. of Electr. Eng., Tokyo Metropolitan Univ., Japan
Volume :
2
fYear :
2000
fDate :
36800
Firstpage :
1703
Abstract :
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
Keywords :
Gaussian distribution; Markov processes; biological organs; biomedical ultrasonics; image sequences; medical image processing; motion estimation; pneumodynamics; statistical analysis; 2-D motion field; Gaussian-Markov random field; computationally stable estimation algorithm; internal organs; parametric estimation; random variables; regression coefficients; respiration; scale factors; spatial constraint; spatial smoothness; spatially smoothed regression model; ultrasonic images; ultrasonography; Equations; Gaussian processes; Gradient methods; Image motion analysis; Image sequences; Medical treatment; Motion estimation; Random processes; Random variables; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Ultrasonics Symposium, 2000 IEEE
Conference_Location :
San Juan
ISSN :
1051-0117
Print_ISBN :
0-7803-6365-5
Type :
conf
DOI :
10.1109/ULTSYM.2000.921650
Filename :
921650
Link To Document :
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