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Use of matched filters for extraction of left ventricular features in two-dimensional short-axis echocardiographic images

机译:使用匹配的滤镜提取二维短轴超声心动图图像中的左心室特征

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Abstract: An automatic method for identification of the center point of the left ventricle of the myocardium during systole is described for 2-dimensional short-axis echocardiographic images. This method, based on the use of large matched filters, identifies a single fixed center point during systole, by locating the three features: the epicardial boundary along the posterior wall, the epicardial boundary along the anterior wall, and the endocardial boundary along the anterior wall. Thus, it provides a first step toward the long term goal of automatic recognition of the endocardial and epicardial boundaries. An index associated with the filter used to approximate the epicardial boundary along the posterior wall provides an indication of the quality of the image and a reliability measurement of the estimate. When tested on 207 image sequences, 18 images were identified by this index (applied to the end diastolic frame) as unsuitable for processing. In the remaining 189 image sequences, 16 of the automatically defined center points were judged poor when compared with estimates made on the end diastolic frame by an independent expert observer. !8
机译:摘要:针对二维短轴超声心动图图像,描述了一种自动识别收缩期心肌左心室中心点的方法。该方法基于大型匹配过滤器的使用,通过定位以下三个特征来确定心脏收缩期的单个固定中心点:沿后壁的心外膜边界,沿前壁的心外膜边界和沿前壁的心内膜边界壁。因此,它为自动识别心内膜和心外膜边界的长期目标提供了第一步。与用于近似沿着后壁的心外膜边界的过滤器相关联的索引提供了图像质量的指示和估计的可靠性测量。当对207个图像序列进行测试时,该索引(应用于舒张末期帧)识别出18个图像不适合处理。在剩下的189个图像序列中,与独立专家观察者对舒张末期框架所做的估计相比,自动定义的中心点中有16个被判定为差。 !8

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