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DORAZIL, J. REPP, R. KROPFREITER, T. PRÜLLER, R. ŘÍHA, K. HLAWATSCH, F.
Original Title
Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion
Type
journal article in Web of Science
Language
English
Original Abstract
Analyzing the motion of the common carotid artery (CCA) wall yields effective indicators for atherosclerosis. In this work, we propose a state-space model and a tracking method for estimating the time-varying CCA wall radius from a B-mode ultrasound sequence of arbitrary length. We employ an unscented Kalman filter that fuses two sets of measurements produced by an optical flow algorithm and a CCA wall localization algorithm. This fusion-and-tracking approach ensures that feature drift, which tends to impair optical flow based methods, is compensated in a temporally consistent manner. Simulation results show that the proposed method outperforms a recently proposed optical flow based method.
Keywords
Atherosclerosis; data fusion; unscented Kalman Filter; motion estimation; ultrasonography; carotid artery; medical imaging; ultrasound imaging
Authors
DORAZIL, J.; REPP, R.; KROPFREITER, T.; PRÜLLER, R.; ŘÍHA, K.; HLAWATSCH, F.
Released
1. 12. 2020
Publisher
IEEE
ISBN
2169-3536
Periodical
IEEE Access
Year of study
8
Number
1
State
United States of America
Pages from
222506
Pages to
222519
Pages count
13
URL
https://doi.org/10.1109/ACCESS.2020.3041796
Full text in the Digital Library
http://hdl.handle.net/11012/196465
BibTex
@article{BUT167451, author="Jan {Dorazil} and Rene {Repp} and Thomas {Kropfreiter} and Richard {Prüller} and Kamil {Říha} and Franz {Hlawatsch}", title="Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion", journal="IEEE Access", year="2020", volume="8", number="1", pages="222506--222519", doi="10.1109/ACCESS.2020.3041796", issn="2169-3536", url="https://doi.org/10.1109/ACCESS.2020.3041796" }