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A New Semi-automated Algorithm for Volumetric Segmentation of the Left Ventricle in Temporal 3D Echocardiography Sequences

机译: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容积分割

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Abstract 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.
机译:摘要 目的 超声心动图是临床上常用的一种无创影像学工具,用于评估心功能。然而,由于超声成像的固有特性,例如存在斑点噪声和低信噪比,左心室的描绘具有挑战性。方法 提出一种半自动分割算法,用于在时间三维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、训练数据或图集的配准。结果 采用加拿大埃德蒙顿Mazankowski阿尔伯塔心脏研究所18例患者的三维超声扫描序列,与心脏病专家提供的手动描绘和其他四种配准算法进行比较。分割方法在心动周期中产生了以下结果:平均绝对差异为 1.01 (0.21) mm,Hausdorff 距离为 4.41 (1.43) mm,骰子重叠评分为 0.93 (0.02)。结论 与其他4种配准算法相比,该方法表现良好。

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