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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Left-Atrial Segmentation From 3-D Ultrasound Using B-Spline Explicit Active Surfaces With Scale Uncoupling
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Left-Atrial Segmentation From 3-D Ultrasound Using B-Spline Explicit Active Surfaces With Scale Uncoupling

机译：使用尺度分离的B样条显式主动曲面从3-D超声进行左心房分割

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摘要

Segmentation of the left atrium (LA) of the heart allows quantification of LA volume dynamics which can give insight into cardiac function. However, very little attention has been given to LA segmentation from three-dimensional (3-D) ultrasound (US), most efforts being focused on the segmentation of the left ventricle (LV). The B-spline explicit active surfaces (BEAS) framework has been shown to be a very robust and efficient methodology to perform LV segmentation. In this study, we propose an extension of the BEAS framework, introducing B-splines with uncoupled scaling. This formulation improves the shape support for less regular and more variable structures, by giving independent control over smoothness and number of control points. Semiautomatic segmentation of the LA endocardium using this framework was tested in a setup requiring little user input, on 20 volumetric sequences of echocardiographic data from healthy subjects. The segmentation results were evaluated against manual reference delineations of the LA. Relevant LA morphological and functional parameters were derived from the segmented surfaces, in order to assess the performance of the proposed method on its clinical usage. The results showed that the modified BEAS framework is capable of accurate semiautomatic LA segmentation in 3-D transthoracic US, providing reliable quantification of the LA morphology and function.
机译：心脏左心房（LA）的分割允许对LA容积动态进行量化，从而可以深入了解心脏功能。但是，对三维（3-D）超声（US）进行的LA分割的关注很少，大部分精力都集中在左心室（LV）的分割上。 B样条显式主动曲面（BEAS）框架已被证明是执行LV分割的一种非常强大且有效的方法。在这项研究中，我们提出了BEAS框架的扩展，引入具有非耦合缩放的B样条。通过对平滑度和控制点数量进行独立控制，此配方改善了对不规则和更多可变结构的形状支持。使用此框架对LA心内膜进行半自动分割的方法是，在对健康受试者的20个超声心动图数据体积序列进行几乎不需要用户输入的情况下进行了测试。分割结果是根据洛杉矶的手动参考轮廓进行评估的。从分割的表面得出相关的LA形态学和功能参数，以评估该方法在临床上的性能。结果表明，改进的BEAS框架能够在3-D经胸US中进行精确的半自动LA分割，从而提供对LA形态和功能的可靠定量。

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