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Discrete and geometric Branch and Bound algorithms for medical image registration

机译:用于医学图像配准的离散和几何分支定界算法

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摘要

Aiming at the development of an exact solution method for registration problems, we present two different Branch & Bound algorithms for a mixed integer programming formulation of the problem. The first B&B algorithm branches on binary assignment variables and makes use of an optimality condition that is derived from a graph matching formulation. The second, geometric B&B algorithm applies a geometric branching strategy on continuous transformation variables. The two approaches are compared for synthetic test examples as well as for 2-dimensional medical data. The results show that medium sized problem instances can be solved to global optimality in a reasonable amount of time.
机译:针对注册问题的精确求解方法的发展,我们针对问题的混合整数编程公式提出了两种不同的Branch&Bound算法。第一个B&B算法在二进制赋值变量上分支,并利用从图匹配公式得出的最优性条件。第二种几何B&B算法对连续变换变量应用几何分支策略。比较了两种方法的综合测试示例以及二维医学数据。结果表明,中等规模的问题实例可以在合理的时间内解决全局最优问题。

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  • 来源
    《Annals of Operations Research》 |2012年第7期|p.737-765|共29页
  • 作者单位

    Institute for Mathematical Optimization, Department of Mathematics, Otto-von-Guericke University Magdeburg, Magdeburg, Germany;

    Department of Mathematics and Informatics, University of Wuppertal, Gaussstr. 20, 42119 Wuppertal,Germany;

    Department of Mathematics and Informatics, University of Wuppertal, Gaussstr. 20, 42119 Wuppertal,Germany;

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