考虑变分图像配准中重叠部分的变化

N. Cahill, J. Noble, D. Hawkes
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引用次数: 1

摘要

用于图像配准的任何相似性度量都以某种方式依赖于描述浮动图像和参考图像之间重叠的区域Ω。在变分配准中,相似度量的g特aux导数驱动配准,大多数文献隐含地假设Ω保持不变。当位移场选择齐次Dirichlet边界条件或滑动边界条件时,此假设成立;但是,如果选择任何其他类型的边界条件,或者如果在重叠区域的某些掩蔽部分上计算相似性度量,则该方法无效。本文说明了如何通过显式地考虑相似度量的gateaux导数中变化的Ω来适应变分配准中不同边界条件和/或屏蔽区域的这些更一般的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accounting for changing overlap in variational image registration
Any similarity measure used for image registration depends in some way on the region Ω describing the overlap between the floating and reference images. In variational registration, where the Gâteaux derivative of the similarity measure drives the registration, most literature implicitly assumes that Ω remains constant. This assumption is valid if homogeneous Dirichlet or sliding boundary conditions are chosen for the displacement field; however, it is invalid if any other type of boundary conditions are chosen, or if the similarity measure is computed over some masked portion of the overlap region. This article illustrates how these more general situations of different boundary conditions and/or masked regions can be accommodated in variational registration by explicitly accounting for the varying Ω in the Gâteaux derivative of the similarity measure.
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