Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion
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 unscent...
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2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9274301/ |
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doaj-372d7d22d9fe4e9289f5fd475b9194ba2021-03-30T04:30:59ZengIEEEIEEE Access2169-35362020-01-01822250622251910.1109/ACCESS.2020.30417969274301Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data FusionJan Dorazil0https://orcid.org/0000-0002-3974-0597Rene Repp1Thomas Kropfreiter2https://orcid.org/0000-0001-7186-7072Richard Pruller3https://orcid.org/0000-0003-3811-2879Kamil Riha4https://orcid.org/0000-0002-6196-5215Franz Hlawatsch5https://orcid.org/0000-0001-9010-9285Institute of Telecommunications, TU Wien, Vienna, AustriaAustrian Academy of Sciences, Acoustics Research Institute, Vienna, AustriaInstitute of Telecommunications, TU Wien, Vienna, AustriaInstitute of Telecommunications, TU Wien, Vienna, AustriaDepartment of Telecommunications, Brno University of Technology, Brno, Czech RepublicInstitute of Telecommunications, TU Wien, Vienna, AustriaAnalyzing 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.https://ieeexplore.ieee.org/document/9274301/Atherosclerosisdata fusionunscented Kalman Filtermotion estimationultrasonographycarotid artery |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Jan Dorazil Rene Repp Thomas Kropfreiter Richard Pruller Kamil Riha Franz Hlawatsch |
| spellingShingle |
Jan Dorazil Rene Repp Thomas Kropfreiter Richard Pruller Kamil Riha Franz Hlawatsch Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion IEEE Access Atherosclerosis data fusion unscented Kalman Filter motion estimation ultrasonography carotid artery |
| author_facet |
Jan Dorazil Rene Repp Thomas Kropfreiter Richard Pruller Kamil Riha Franz Hlawatsch |
| author_sort |
Jan Dorazil |
| title |
Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion |
| title_short |
Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion |
| title_full |
Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion |
| title_fullStr |
Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion |
| title_full_unstemmed |
Tracking Carotid Artery Wall Motion Using an Unscented Kalman Filter and Data Fusion |
| title_sort |
tracking carotid artery wall motion using an unscented kalman filter and data fusion |
| publisher |
IEEE |
| series |
IEEE Access |
| issn |
2169-3536 |
| publishDate |
2020-01-01 |
| description |
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. |
| topic |
Atherosclerosis data fusion unscented Kalman Filter motion estimation ultrasonography carotid artery |
| url |
https://ieeexplore.ieee.org/document/9274301/ |
| work_keys_str_mv |
AT jandorazil trackingcarotidarterywallmotionusinganunscentedkalmanfilteranddatafusion AT renerepp trackingcarotidarterywallmotionusinganunscentedkalmanfilteranddatafusion AT thomaskropfreiter trackingcarotidarterywallmotionusinganunscentedkalmanfilteranddatafusion AT richardpruller trackingcarotidarterywallmotionusinganunscentedkalmanfilteranddatafusion AT kamilriha trackingcarotidarterywallmotionusinganunscentedkalmanfilteranddatafusion AT franzhlawatsch trackingcarotidarterywallmotionusinganunscentedkalmanfilteranddatafusion |
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1724181632597884928 |