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Delaunay-Based Vector Segmentation of Volumetric Medical Images

机译:基于Delaunay的体积医学图像矢量分割

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摘要

The image segmentation plays an important role in medical image processing. Many segmentation algorithms exist. Most of them produce raster data which is not suitable for 3D geometrical modeling of human tissues. In this paper, a vector segmentation algorithm based on a 3D Delaunay triangulation is proposed. Tetrahedral mesh is used to divide a volumetric CT/MR data into non-overlapping regions whose characteristics are similar. Novel methods for improving quality of the mesh and its adaptation to the image structure are also presented.
机译:图像分割在医学图像处理中起着重要的作用。存在许多分割算法。它们中的大多数产生的栅格数据不适合人体组织的3D几何建模。本文提出了一种基于3D Delaunay三角剖分的矢量分割算法。四面体网格用于将体积CT / MR数据划分为特征相似的非重叠区域。还提出了提高网格质量及其对图像结构的适应性的新方法。

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