Feature Drift Resilient Tracking of the Carotid Artery Wall Using Unscented Kalman Filtering With Data Fusion
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU136636" target="_blank" >RIV/00216305:26220/20:PU136636 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICASSP40776.2020.9054703" target="_blank" >https://doi.org/10.1109/ICASSP40776.2020.9054703</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP40776.2020.9054703" target="_blank" >10.1109/ICASSP40776.2020.9054703</a>
Alternative languages
Result language
angličtina
Original language name
Feature Drift Resilient Tracking of the Carotid Artery Wall Using Unscented Kalman Filtering With Data Fusion
Original language description
An analysis of the motion of the common carotid artery (CCA) provides effective indicators for cardiovascular diseases. Here, we propose a method for tracking CCA wall motion from a B-mode ultrasound video sequence. An unscented Kalman filter based on a suitably devised state-space model fuses measurements produced by an optical flow algorithm and a CCA wall localization algorithm. This approach compensates for feature drift, which is a detrimental effect in optical flow algorithms. The proposed method is demonstrated to outperform a state-of-the-art tracking method based on optical flow.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20601 - Medical engineering
Result continuities
Project
<a href="/en/project/GA17-19638S" target="_blank" >GA17-19638S: Sequential Bayesian Estimation of Arterial Wall Motion</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ISBN
978-1-5090-6631-5
ISSN
0736-7791
e-ISSN
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Number of pages
5
Pages from-to
1095-1099
Publisher name
Neuveden
Place of publication
Neuveden
Event location
Barcelona
Event date
May 4, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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