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首页> 外文期刊>IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics >A new method for analyzing local shape in three-dimensional images based on medial axis transformation
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A new method for analyzing local shape in three-dimensional images based on medial axis transformation

机译：基于中间轴变换的三维图像局部形状分析新方法

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摘要

In this paper, we propose a new approach based on three-dimensional (3-D) medial axis transformation for describing geometrical shapes in three-dimensional images. For 3-D-images, the medial axis, which is composed of both curves and medial surfaces, provides a simplified and reversible representation of structures. The purpose of this new method is to classify each voxel of the three-dimensional images in four classes: boundary, branching, regular and arc points. The classification is first performed on the voxels of the medial axis. It relies on the topological properties of a local region of interest around each voxel. The size of this region of interest is chosen as a function of the local thickness of the structure. Then, the reversibility of the medial axis is used to deduce a labeling of the whole object. The proposed method is evaluated on simulated images. Finally, we present an application of the method to the identification of bone structures from 3-D very high-resolution tomographic images.
机译：在本文中，我们提出了一种基于三维（3-D）中轴变换的新方法来描述三维图像中的几何形状。对于3-D图像，由曲线和内侧表面组成的内侧轴提供了结构的简化且可逆的表示。这种新方法的目的是将三维图像的每个体素分为四类：边界点，分支点，规则点和弧点。首先在中轴的体素上执行分类。它依赖于每个体素周围感兴趣的局部区域的拓扑特性。选择该感兴趣区域的大小作为结构局部厚度的函数。然后，使用中轴的可逆性来推断整个对象的标签。在模拟图像上评估了所提出的方法。最后，我们介绍了该方法在从3-D超高分辨率断层图像中识别骨骼结构的应用。

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