Tracking Carotid Artery Wall Motion Using An Unscented Kalman Filter And Data Fusion
IEEE ACCESS(2020)
摘要
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.
更多查看译文
关键词
Tracking,Ultrasonic imaging,Speckle,Adaptive optics,State-space methods,Optical filters,Kalman filters,Atherosclerosis,data fusion,unscented Kalman Filter,motion estimation,ultrasonography,carotid artery,medical imaging,ultrasound imaging
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要