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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Medical image segmentation, volume representation and registration using spheres in the geometric algebra framework
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Medical image segmentation, volume representation and registration using spheres in the geometric algebra framework

机译:在几何代数框架中使用球体进行医学图像分割,体积表示和配准

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摘要

This paper presents an algorithm to model volumetric data and other one for non-rigid registration of such models using spheres formulated in the geometric algebra framework. The proposed algorithm for modeling, as opposite to the Union of Spheres method, reduces the number of entities (spheres) used to model 3D data. Our proposal is based in marching cubes idea using, however, spheres, while the Union of Spheres uses Delaunay tetrahedrization. The non-rigid registration is accomplished in a deterministic annealing scheme. At the preprocessing stage we segment the objects of interest by a segmentation method based on texture information. This method is embedded in a region growing scheme. As our final application, we present a scheme for surgical object tracking using again geometric algebra techniques. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
机译:本文提出了一种使用几何代数框架中制定的球体对体积数据进行建模的算法,以及用于非刚性配准此类模型的另一种算法。与球体联合方法相反,所提出的建模算法减少了用于对3D数据建模的实体(球体)的数量。我们的建议基于使用球体来推进立方体思想,而球体联合体则使用Delaunay四面体化。非刚性配准是在确定性退火方案中完成的。在预处理阶段,我们通过基于纹理信息的分割方法对感兴趣的对象进行分割。该方法嵌入在区域增长方案中。作为我们的最终应用,我们提出了一种使用几何代数技术再次跟踪手术对象的方案。 (c)2006模式识别学会。由Elsevier Ltd.出版。保留所有权利。

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