Paper Info
Title
A Multitarget Tracking Method For Estimating Carotid Artery Wall Motion From Ultrasound Sequences
Abstract
Analyzing the motion of the wall of the common carotid artery (CCA) yields effective indicators for atherosclerosis. In this work, we explore the use of multitarget tracking techniques for estimating the time-varying CCA radius from an ultrasound video sequence. We employ the joint integrated probabilistic data association (JIPDA) filter to track a set of "feature points" (FPs) located around the CCA wall cross section. Subsequently, we estimate the time-varying CCA radius via a nonlinear least-squares method and a Kalman filter. The application of the JIPDA filter is enabled by a linearized state-space model describing the quasi-periodic movement of the FPs and the measurement extraction process. Simulation results using the Field II ultrasound simulation program show that the proposed multitarget tracking method can outperform a state-of-the-art method.
Year
DOI
Venue
2019
10.23919/EUSIPCO.2019.8902772
2019 27TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO)
Keywords
Field
DocType
Atherosclerosis, common carotid artery, ultrasound video processing, speckle tracking, multitarget tracking, joint integrated probabilistic data association (JIPDA) filter
Computer vision,Computer science,Carotid arteries,Kalman filter,Data association,Artificial intelligence,Probabilistic logic,Common carotid artery,Ultrasound
Conference
ISSN
Citations 
PageRank 
2076-1465
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Jan Dorazil101.69
Rene Repp211.02
Thomas Kropfreiter3373.19
Richard Prüller400.34
Kamil Ríha52313.58
Franz Hlawatsch61288118.49