Purpose

Echocardiography is commonly used as a non-invasive imaging tool in clinical practice for the assessment of cardiac function. However, delineation of the left ventricle is challenging due to the inherent properties of ultrasound imaging, such as the presence of speckle noise and the low signal-to-noise ratio.

Methods

We propose a semi-automated segmentation algorithm for the delineation of the left ventricle in temporal 3D echocardiography sequences. The method requires minimal user interaction and relies on a diffeomorphic registration approach. Advantages of the method include no dependence on prior geometrical information, training data, or registration from an atlas.

Results

The method was evaluated using three-dimensional ultrasound scan sequences from 18 patients from the Mazankowski Alberta Heart Institute, Edmonton, Canada, and compared to manual delineations provided by an expert cardiologist and four other registration algorithms. The segmentation approach yielded the following results over the cardiac cycle: a mean absolute difference of 1.01 (0.21) mm, a Hausdorff distance of 4.41 (1.43) mm, and a Dice overlap score of 0.93 (0.02).

Conclusion

The method performed well compared to the four other registration algorithms.

中文翻译：

---

一种新的半自动算法，用于在时间 3D 超声心动图序列中对左心室进行体积分割

目的

超声心动图通常用作临床实践中评估心脏功能的非侵入性成像工具。然而，由于超声成像的固有特性，例如存在散斑噪声和低信噪比，左心室的描绘具有挑战性。

方法

我们提出了一种半自动分割算法，用于在时间 3D 超声心动图序列中描绘左心室。该方法需要最少的用户交互并依赖于微分配准方法。该方法的优点包括不依赖于先前的几何信息、训练数据或来自图谱的注册。

结果

该方法使用来自加拿大埃德蒙顿 Mazankowski Alberta 心脏研究所的 18 名患者的 3D 超声扫描序列进行了评估，并与专家心脏病专家提供的手动描绘和其他四种配准算法进行了比较。分割方法在心动周期内产生以下结果：平均绝对差为 1.01 (0.21) mm，Hausdorff 距离为 4.41 (1.43) mm，Dice 重叠得分为 0.93 (0.02)。

结论

与其他四种配准算法相比，该方法表现良好。