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A unified information-theoretic approach to the correspondence problem in image registration

机译:图像配准中对应问题的统一信息论方法

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We consider the correspondence problem associated with the non-rigid registration of a group of images; in particular, the theoretical basis for the derivation of the objective function that defines the 'best' correspondence across a set of images. For intra-subject registration, there is an actual physical deformation process underlying the observed deformation, but for inter-subject registration, there is no such physical process, and hence no hypothetical process that generates the observed data. This leads to the conclusion that our constructions should be based on the data alone. Such a construction is possible using criteria derived from information theory. We show how many commonly used pairwise voxel-based similarity measures can be generated using these criteria, and discuss how this approach can be extended to give a unified theoretical basis for the generation of novel objective functions in the groupwise case, where both image discrepancy and image deformation terms are included in a principled way.
机译:我们考虑与一组图像的非刚性配准相关的对应问题;尤其是推导定义一组图像中“最佳”对应关系的目标函数的理论基础。对于受试者内部配准,在观察到的变形的基础上存在实际的物理变形过程,但是对于受试者间配准,则没有这样的物理过程,因此也没有生成观察到的数据的假设过程。由此得出结论,我们的构造应仅基于数据。使用从信息理论得出的标准,这种构造是可能的。我们展示了使用这些标准可以生成多少个常用的基于成对的基于体素的相似性度量,并讨论了如何扩展这种方法以为在成组情况下生成新颖目标函数提供统一的理论基础,在这种情况下,图像差异和原则上包括图像变形项。

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