School of Computer Science, University of Lincoln, Lincoln, UK.
National Heart and Lung Institute, Imperial College London, London, UK.
Med Biol Eng Comput. 2020 Jun;58(6):1309-1323. doi: 10.1007/s11517-020-02142-8. Epub 2020 Apr 7.
Speckle tracking is the most prominent technique used to estimate the regional movement of the heart based on echocardiograms. In this study, we propose an optimised-based block matching algorithm to perform speckle tracking iteratively. The proposed technique was evaluated using a publicly available synthetic echocardiographic dataset with known ground-truth from several major vendors and for healthy/ischaemic cases. The results were compared with the results from the classic (standard) two-dimensional block matching. The proposed method presented an average displacement error of 0.57 pixels, while classic block matching provided an average error of 1.15 pixels. When estimating the segmental/regional longitudinal strain in healthy cases, the proposed method, with an average of 0.32 ± 0.53, outperformed the classic counterpart, with an average of 3.43 ± 2.84. A similar superior performance was observed in ischaemic cases. This method does not require any additional ad hoc filtering process. Therefore, it can potentially help to reduce the variability in the strain measurements caused by various post-processing techniques applied by different implementations of the speckle tracking. Graphical Abstract Standard block matching versus proposed iterative block matching approach.
斑点追踪是基于超声心动图估计心脏区域运动的最突出技术。在这项研究中，我们提出了一种基于优化的块匹配算法来进行斑点追踪的迭代。所提出的技术使用来自几个主要供应商的具有已知真实情况的公开可用的合成超声心动数据集进行了评估，并针对健康/缺血病例进行了评估。将结果与经典（标准）二维块匹配的结果进行了比较。该方法的平均位移误差为 0.57 像素，而经典块匹配的平均误差为 1.15 像素。在估计健康病例的节段/区域纵向应变时，该方法的平均值为 0.32 ± 0.53，优于经典方法的平均值 3.43 ± 2.84。在缺血病例中也观察到类似的优越性能。该方法不需要任何额外的特殊滤波过程。因此，它可以帮助减少由于斑点追踪的不同实现所应用的各种后处理技术而导致的应变测量中的可变性。
