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- 2017
基于散斑跟踪技术的超声心动图心动周期估计
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Abstract:
摘要： 基于块匹配散斑跟踪技术,提出估计超声心动图心动周期的方法。选择超声心动图心肌壁中感兴趣区域(region of interest, ROI),跟踪和记录每帧超声图像上ROI区域内心肌组织上的散斑或散斑模式的位置和运动。通过计算ROI区域内散斑的位移,用最小绝对误差和(sum of absolute differences, SAD)算法估计心动周期的长度和起点,并用仿真超声序列图像对方法进行验证。试验结果表明超声心动图心动周期的理论值与实际值有较高的一致性。该方法能够有效、可靠地估计心动周期长度和起点。
Abstract: A cardiac cycle estimation method of echocardiography was proposed based on block matching speckle tracking. The position and movement of speckles or speckle pattern within the area of myocardial tissue on echocardiographic images was tracked and recorded, by selecting the regions of interest(ROI)inside the myocardial wall. By calculating the displacement of speckles in the ROI, the length and the start of cardiac cycle was estimated with the sum of absolute differences(SAD)algorithm, and the method was validated by simulated echocardiographic sequences. The experiment results showed a high consistency between theoretical values and actual ones of the cardiac cycle. This method could estimate the length and the start of cardiac cycle effectively and reliably
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