Automatic estimation of left ventricular dysfunction from echocardiogram videos

D. Beymer, T. Syeda-Mahmood, A. Amir, Fei Wang, Scott Adelman
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引用次数: 15

Abstract

Echocardiography is often used to diagnose cardiac diseases related to regional and valvular motion abnormalities. Due to the low resolution of the imaging modality, the choice of viewpoint and mode, and the experience of the sonographers, there is a large variance in the estimation of important diagnostic measurements such as ejection fraction. In this paper, we develop an automatic algorithm to estimate diagnostic measurements from raw echocardiogram video sequences. Specifically, we locate and track the left ventricular region over a heart cycle using active shape models. We also present efficient ventricular localization in video sequences by automatically detecting and propagating echocardiographer annotations. Results on a large database of cardiac echo videos demonstrate the use of our method for the prediction of left ventricular dysfunction.
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从超声心动图视频自动估计左心室功能障碍
超声心动图常用于诊断与局部和瓣膜运动异常有关的心脏疾病。由于成像方式的低分辨率、视点和模式的选择以及超声医师的经验,在诸如射血分数等重要诊断测量值的估计上存在很大差异。在本文中,我们开发了一种从原始超声心动图视频序列中估计诊断测量的自动算法。具体来说,我们定位和跟踪左心室区域在一个心脏周期使用主动形状模型。我们还通过自动检测和传播超声心动图注释,在视频序列中提出了有效的心室定位。结果在一个大型数据库的心脏回声视频证明使用我们的方法来预测左心室功能障碍。
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