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Estimating Peak Velocity Profiles from Doppler Echocardiography using Digital Image Processing

机译:使用数字图像处理估计多普勒超声心动图的峰值速度谱

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This study aims at developing a digital signal processing algorithm to extract positive and negative peak velocity profiles from Doppler echocardiographic images. These profiles are useful in estimating cardiac time intervals and establishing realistic boundary conditions for computational hemodynamic studies. The proposed image processing algorithm is based on two different thresholding methods. The histograms of image intensity function were used to help threshold values selection so that the algorithm yields velocity profiles properly represent Doppler shift envelopes. One of the thresholding methods tended to provide the lower-limit (i.e. underestimate) of the velocity profile, while the second tended to provide the upper-limit of the velocity profile (i.e., overestimate). The final peak velocity profiles were estimated from the combination of the estimates from both thresholding methods. The peak velocity profiles were then qualitatively compared with the results of the standard edge detection methods such as Canny and Prewitt approximations. The proposed automated approach might be helpful for objective estimation of peak velocities and cardiac time intervals.
机译:该研究旨在开发数字信号处理算法,以从多普勒超声心动图图像中提取正极和负峰值速度谱。这些简档可用于估计心脏时间间​​隔并建立用于计算血流动力学研究的现实边界条件。所提出的图像处理算法基于两种不同的阈值处理方法。图像强度函数的直方图用于帮助阈值选择,使得算法能够适当地表示速度分布代表多普勒换档信封。其中一个阈值方法倾向于提供速度曲线的下限(即低估),而第二则倾向于提供速度曲线(即,高估)的上限。最终峰值速度分布从阈值方法的估计的组合估计。然后与标准边缘检测方法(如Canny和Prowitt近似)的结果进行比较峰值速度分布。所提出的自动化方法可能有助于客观估计峰值速度和心脏时间间​​隔。

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