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A new method for nonrigid registration of three-dimensional images.

机译:一种非刚性的三维图像配准的新方法。

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摘要

In this dissertation we present a novel method for the nonrigid registration of 3D images using a well-established mathematical framework mostly known as the deformation based grid generation method. The deformation based grid generation method is able to generate a grid with desired grid density distribution that is free from grid folding. This method gives direct control over the cell size of the adaptive grid and determines the node velocities directly. The adaptive grid system naturally distributes more grids to deprived areas. The positive monitor function disallows grid folding and provides a mean to control the ratio of the areas between the original and transformed domain. Based on these, we have successfully developed a new non-rigid registration method that has many advantages: Firstly, it is based on a solid mathematical foundation. In particular, it accounts for local volume changes through the divergence of the transformation; and it accounts for local rotation through the curl vector of the transformation. Secondly, the method is based on a linear differential system; its numerical implementation is fast, stable, simple and robust. Thirdly, it does not require to use of any regularization term. Finally, the method is general in the sense that it may be used in any optimization problem that involves motion estimation. Thus, it has the potential to be the numerical kernel for a wide range of applications.
机译:在本文中,我们提出了一种使用成熟的数学框架(通常称为基于变形的网格生成方法)进行3D图像非刚性配准的新方法。基于变形的网格生成方法能够生成具有所需网格密度分布且没有网格折叠的网格。该方法直接控制自适应网格的像元大小,并直接确定节点速度。自适应网格系统自然会将更多网格分布到贫困地区。正监视功能不允许网格折叠,并且提供了一种方法来控制原始域和变换域之间的面积比。基于这些,我们成功开发了一种具有许多优点的新的非刚性配准方法:首先,它基于扎实的数学基础。尤其是,它通过转换的差异来说明本地量的变化;并通过转换的卷曲向量说明局部旋转。其次,该方法基于线性微分系统。它的数值实现是快速,稳定,简单和可靠的。第三,它不需要使用任何正则化术语。最后,在可以将其用于涉及运动估计的任何优化问题的意义上,该方法是通用的。因此,它有可能成为广泛应用的数字内核。

著录项

  • 作者

    Akinlar, Mehmet Ali.;

  • 作者单位

    The University of Texas at Arlington.;

  • 授予单位 The University of Texas at Arlington.;
  • 学科 Mathematics.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 54 p.
  • 总页数 54
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 数学;
  • 关键词

  • 入库时间 2022-08-17 11:37:37

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