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Medical Image Segmentation and the Use of Geometric Algebras in Medical Applications

机译:医学图像分割与医疗应用中几何代数的使用

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This paper presents a method for segmentation of medical images and the application of the so called geometric or Clifford algebras for volume representation, non-rigid registration of volumes and object tracking. Segmentation is done combining texture and boundary information in a region growing strategy obtaining good results. To model 2D surfaces and 3D volumetric data we present a new approach based on marching cubes idea however using spheres. We compare our approach with other method based on the delaunay tetrahedrization. The results show that our proposed approach reduces considerably the number of spheres. Also we show how to do non-rigid registration of two volumetric data represented as sets of spheres using 5-dimensional vectors in conformal geometric algebra. Finally we show the application of geometric algebras to track surgical devices in real time.
机译:本文提出了一种用于分割医学图像的方法,以及所谓的几何或夹轴代数用于体积表示,卷的非刚性登记和物体跟踪的应用。分割是组合在地区生长策略中的纹理和边界信息获得良好结果。模拟2D表面和3D容量数据,我们介绍了一种基于游行立方体思想的新方法,然而使用球形。我们将采用基于Delaunay四元化的其他方法进行比较。结果表明,我们的建议方法显着降低了球体的数量。此外,我们还展示了如何在共形几何代数中使用5维矢量来做两个容积数据的非刚性注册,其中包括用于共形几何代数的5维向量。最后,我们展示了几何代数的应用实时跟踪手术器件。

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