Automatic segmentation of echocardiographic sequences by active appearance motion models
Automatic segmentation of echocardiographic sequences by active appearance motion models
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DOI：
10.1109/tmi.2002.806427
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发表时间：
2002-11-01
影响因子：
10.6
通讯作者：
Reiber, JHC
中科院分区：
文献类型：
--
作者：
Bosch, JG;Mitchell, SC;Reiber, JHC
本文提出了一种新的主动外观模型（AAM）扩展，用于超声心动图图像序列中的自动边界检测。主动外观运动模型（AAMM）技术允许在整个心动周期内全自动、鲁棒和时间连续描绘左心室（LV）内膜轮廓，效果良好。开发了非线性强度归一化，并用于适应超声特异性强度分布。该方法在129例脑梗死患者的16帧相位标准化经胸四腔序列上进行训练和测试，随机分为训练集（n = 65）和测试集（n = 64）。将边界与专家绘制的内膜轮廓进行比较。在测试集上，全自动AAMM在97%的情况下表现良好（手动和自动标志点之间的平均距离为3.3 mm，与人类观察者间的差异相当）。超声特异性强度标准化被证明对超声心动图的良好结果具有重要价值。的AAMM是显着更准确的比一组等效的二维AAM。
A novel extension of active appearance models (AAMs) for automated border detection in echocardiographic image sequences is reported. The active appearance motion model (AAMM) technique allows fully automated robust and time-continuous delineation of left ventricular (LV) endocardial contours over the full heart cycle with good results. Nonlinear intensity normalization was developed and employed to accommodate ultrasound-specific intensity distributions. The method was trained and tested on 16-frame phase-normalized transthoracic four-chamber sequences of 129 unselected infarct patients, split randomly into a training set (n = 65) and a test set (n = 64). Borders were compared to expert drawn endocardial contours. On the test set, fully automated AAMM performed well in 97% of the cases (average distance between manual and automatic landmark points was 3.3 mm, comparable to human interobserver variabilities). The ultrasound-specific intensity normalization proved to be of great value for good results in echocardiograms. The AAMM was significantly more accurate than an equivalent set of two-dimensional AAMs.