Tracking of Heart Wall Motion using Unscented Kalman Filter

D. Hazarika, C. Mahanta, S. Dandapat
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Abstract

We propose a semiautomatic method based on unscented Kalman filter (UKF) to track left ventricular heart wall motion from a series of echocardiographic images. Our method requires manual drawing of contour on the first frame of the image sequence to represent the left ventricle boundary. Heart wall tracking from echocardiographic image is a difficult task because of poor signal-to-noise ratio and presence of speckle noise. For speckle noise removal adaptive weighted median filter is used. Tracking results obtained by using our proposed UKF based method are compared with results obtained by using Kalman filter (KF) based tracker. The root mean square error (RMSE) between actual and tracked boundary of the heart wall is calculated for each pixel using both these methods. It is observed that RMSE produced by UKF based tracker is less than that produced by KF based tracker
利用无气味卡尔曼滤波跟踪心壁运动
提出了一种基于无气味卡尔曼滤波(UKF)的半自动方法,从一系列超声心动图图像中跟踪左心室心壁运动。我们的方法需要在图像序列的第一帧上手工绘制轮廓来表示左心室边界。由于超声心动图图像的信噪比较低和存在斑点噪声,心壁跟踪是一项困难的任务。对散斑噪声的去除采用自适应加权中值滤波。将基于UKF的跟踪结果与基于卡尔曼滤波(KF)的跟踪结果进行了比较。利用这两种方法计算每个像素点心壁实际边界和跟踪边界的均方根误差(RMSE)。观察到基于UKF的跟踪器产生的RMSE小于基于KF的跟踪器产生的RMSE
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