Dorazil, J., Repp, R., Kropfreiter, T., Prüller, R., Říha, K., & Hlawatsch, F. (2020). Tracking carotid artery wall motion using an unscented Kalman filter and data fusion. IEEE Access, 8, 222506–222519. https://doi.org/10.1109/access.2020.3041796
General Computer Science; General Engineering; General Materials Science; data fusion; Atherosclerosis; unscented Kalman Filter; motion estimation; ultrasonography; carotid artery; medical imaging; ultrasound imaging
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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.
