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Landmark-Based Non-rigid Registration Via Graph Cuts

机译:通过图割的基于地标的非刚性配准

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This paper presents an approach based on graph cuts initially used for motion segmentation that is being applied to the non-rigid registration problem. The main contribution of our method is the formulation of landmarks in the graph cut minimization framework. In the graph cut method, we add a penalty cost based on landmarks to the data energy. In the presence of a landmark, we adjust the T-link weights to cut strategic links. Our formulation also allows the spread of a landmark influence to its neighborhood. We first show with synthetic images that minimization with graph cuts can indeed be used for non-rigid registration and show how landmarks can guide the minimization process towards a customized solution. We later use this method with real images and show how landmarks can successfully guide the registration of a coronary angiogram.
机译:本文提出了一种基于最初用于运动分割的图割的方法,该方法已应用于非刚性配准问题。我们方法的主要贡献是在图形切割最小化框架中制定了界标。在图割方法中,我们将基于界标的惩罚成本添加到数据能量中。在存在地标的情况下,我们调整T形链接的权重以切断战略链接。我们的提法还允许将具有里程碑意义的影响力传播到附近地区。我们首先使用合成图像显示使用图形切割最小化的确可以用于非刚性配准,并显示界标如何引导最小化过程走向定制解决方案。我们稍后将这种方法与实际图像一起使用,并显示界标如何成功地指导冠状动脉造影的注册。

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