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Automatic detection of left ventricular aneurysms in echocardiograms

机译:超声心动图中左心室动脉瘤的自动检测

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Left ventricular cardiac aneurysms are bulgings in the myocardium muscle of the left ventricle. These irregular distortions of the left ventricular shape from its normal bullet-like appearance, are often due to result of myocardial infarction and can be fatal. In this paper we address, for the first time, the automatic detection of left ventricular (LV) cardiac aneurysms from 4-chamber views in echocardiograms. For this, we first detect the left ventricle in the echocardiogram image as the lumen region closest to the apex of the heart. The apex itself is estimated from the bounding lines of the viewing sector in an echocardiogram. The boundary of the LV is then analyzed to extract key curvature-based features for discrimination using a support vector machine with radial basis function kernels. Results of testing on a large echocardiogram video collection indicate that robust detection of left ventricle coupled with curvature features is sufficient to reliably separate LV aneurysms from normal left ventricular shapes.
机译:左心室心肌动脉瘤是左心室的心肌肌肉中的碎片。这些不规则的扭曲左心室形状从其正常的子弹状外观,往往是由于心肌梗死的结果,并且可能是致命的。在本文中,我们首次解决了从超声心动图中的4室视图自动检测左心室(LV)心脏动脉瘤。为此,我们首先检测超声心动图图像中的左心室,因为最接近心脏顶点的内腔区域。顶点本身估计超声心动图中观看扇区的边界线。然后分析LV的边界以利用具有径向基函数内核的支持向量机来提取基于关键的基于曲率的特征。大超声心动图的测试结果表明,左心室与曲率特征耦合的鲁棒检测足以使LV动脉瘤与正常左心室形状可靠地分离。

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