TY - GEN
T1 - A sequential Bayesian based method for tracking and strain palpography estimation of arteries in intravascular ultrasound images
AU - Widynski, Nicolas
AU - Porée, Jonathan
AU - Roy Cardinal, Marie Hélène
AU - Ohayon, Jacques
AU - Cloutier, Guy
AU - Garcia, Damien
N1 - Publisher Copyright:
© 2014 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2014/10/20
Y1 - 2014/10/20
N2 - This paper investigates the task of tracking and strain estimation of arteries in intravascular ultrasound images. A tracking method is proposed to extract the inner and the outer contours of the vessel wall (lumen/intima-media and intima-media/adventitia interfaces, respectively), and the deformations along them. This estimation is carried out by a non parametric sequential Bayesian method. The Bayesian modeling holds three ingredients: the prior, which is given by a manually defined segmentation of the contours on the first image; the transition, which is assumed to follow a Markovian random walk; and the likelihood, which is a distance between patches distributed along the contours. The underlying Bayesian posterior distribution is approximated using a sequential Monte Carlo approach. Experiments on three PVA-C phantoms present direct readings of the deformations along the lumen/intima-media contour.
AB - This paper investigates the task of tracking and strain estimation of arteries in intravascular ultrasound images. A tracking method is proposed to extract the inner and the outer contours of the vessel wall (lumen/intima-media and intima-media/adventitia interfaces, respectively), and the deformations along them. This estimation is carried out by a non parametric sequential Bayesian method. The Bayesian modeling holds three ingredients: the prior, which is given by a manually defined segmentation of the contours on the first image; the transition, which is assumed to follow a Markovian random walk; and the likelihood, which is a distance between patches distributed along the contours. The underlying Bayesian posterior distribution is approximated using a sequential Monte Carlo approach. Experiments on three PVA-C phantoms present direct readings of the deformations along the lumen/intima-media contour.
UR - http://www.scopus.com/inward/record.url?scp=84910097032&partnerID=8YFLogxK
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U2 - 10.1109/ULTSYM.2014.0127
DO - 10.1109/ULTSYM.2014.0127
M3 - Conference contribution
AN - SCOPUS:84910097032
T3 - IEEE International Ultrasonics Symposium, IUS
SP - 515
EP - 518
BT - IEEE International Ultrasonics Symposium, IUS
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Ultrasonics Symposium, IUS 2014
Y2 - 3 September 2014 through 6 September 2014
ER -