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首页> 外文会议>6th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2003) Pt.II; Nov 15-18, 2003; Montreal, Canada >Grid Refinement in Adaptive Non-rigid Registration
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Grid Refinement in Adaptive Non-rigid Registration

机译：自适应非刚性配准中的网格细化

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摘要

Non-rigid mutual information (MI) registration algorithms with many degrees of freedom (DOF) are quite useful, but they come at high computational cost and have convergence issues. As a remedy adaptive non-rigid registration algorithms, where DOF is increased adaptively (i.e. the grid is refined adaptively), have been proposed. There are at least two ways to refine a grid adaptively: one based on changes in the global measure, the other based on a local measure. We compare these two and show that a local measure method can have better sensitivity to deformations than the global measure. The local measure employed is a novel method using local entropies and local MI.
机译：具有多个自由度（DOF）的非刚性互信息（MI）注册算法非常有用，但是它们的计算成本很高，并且存在收敛问题。作为一种补救性自适应非刚性配准算法，已经提出了DOF自适应地增加（即，网格被自适应地改进）的方法。至少有两种方法可以自适应地优化网格：一种基于全局度量的更改，另一种基于局部度量。我们将这两者进行比较，结果表明，局部测量方法比整体测量方法对变形的敏感性更高。所采用的局部度量是一种使用局部熵和局部MI的新颖方法。

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