一种基于水平集的计算效率高的形状分析方法

Zsofia Tari, J. Shah, H. Pien
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引用次数: 35

摘要

近年来,曲线演化已被应用于形状平滑和形状分析,特别是在生物医学图像分析中取得了相当大的成功。多尺度分析提供了关于形状的部分、它们的轴或中心以及形状骨架的信息。在这里,作者表明,边缘强度函数的水平集提供了本质上相同的形状分析提供了曲线演化。与曲线演化法相比,该方法具有若干优点。由于控制方程是线性的,因此实现更简单、更快。同样的方程也适用于高维问题。一个重要的优点是,不同于曲线演化的方法,新方法适用于形状可能有连接点,如三重点。边缘强度可以在不首先提取形状轮廓的情况下从原始图像计算。因此,该方法可以应用于原始图像。该方法提供了一种在一个通用的集成框架内处理分割问题和形状分析的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A computationally efficient shape analysis via level sets
In recent years, curve evolution has been applied to smoothing of shapes and shape analysis with considerable success, especially in biomedical image analysis. The multiscale analysis provides information regarding parts of shapes, their axes or centers and shape skeletons. Here, the authors show that the level sets of an edge-strength function provide essentially the same shape analysis as provided by curve evolution. The new method has several advantages over the method of curve evolution. Since the governing equation is linear, the implementation is simpler and faster. The same equation applies to problems of higher dimension. An important advantage is that unlike the method of curve evolution, the new method is applicable to shapes which may have junctions such as triple points. The edge-strength may be calculated from raw images without first extracting the shape outline. Thus the method can be applied to raw images. The method provides a way to approach the segmentation problem and shape analysis within a common integrated framework.
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