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Enhanced Endocardial Boundary Detection in Echocardiography Images Using B-Spline and Statistical Method

机译:使用B样条和统计方法增强超声心动图图像的心内膜边界

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摘要

Extraction of endocardial motion is important to provide more accurate myocardial motion for further cardiac image analysis. This process involves endocardial detection which is challenging due to the presence of speckle noise and discontinuities of endocardial boundary. Researchers actively investigate various approaches to perform endocardial detection even though they involve extensive computations task and time consuming. In this paper, we implement a basic edge map detection using gradient and cavity-center-based method to detect the endocardial boundary. This method produces a boundary which still has discontinuities and outlier coordinates. To enhance the boundary, we propose a method based on a B-Spline and statistical approach to remove the discontinous points along the endocardium on parasternal short axis view of cardiac. The proposed method produces results which give visual evidences that it is able to significantly enhance the endocardial boundary.
机译:心内膜运动的提取对于为进一步的心脏图像分析提供更准确的心肌运动很重要。该过程涉及心内膜检测,这由于斑点噪声的存在和心内膜边界的不连续而具有挑战性。研究人员积极研究执行心内膜检测的各种方法,即使它们涉及大量的计算任务和耗时的时间。在本文中,我们使用梯度和基于腔心的方法实现了基本的边缘图检测,以检测心内膜边界。这种方法产生的边界仍然具有不连续性和离群坐标。为了增强边界,我们提出了一种基于B样条和统计方法的方法,以消除心脏旁胸骨短轴视图上沿心内膜的不连续点。所提出的方法产生的结果提供了视觉证据,表明它能够显着增强心内膜边界。

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