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首页> 外文期刊>Journal of fiber bioengineering and informatics >Performance Comparison of Optimization Methods for Medical Image Registration*
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Performance Comparison of Optimization Methods for Medical Image Registration*

机译：医学图像配准优化方法的性能比较*

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摘要

In the process of medical image registration, the registration function (also so-called similarity metric) was taken as the objective function, and the multi-parameter optimization method as the tool for obtaining the optimal transformation parameters. In this paper, by the use of the mutual information as the registration function, the Powell method and the genetic algorithm were exerted to explore the optimal transformation parameters respectively, and their optimizing performances were evaluated and compared. The experimental results reveal that the Powell method can cater to both the mono- and multi-modality medical image registrations. Unfortunately, however, the genetic algorithm is not adopted for the medical image registration regardless of the registration accuracy or the running time and needs to be significantly improved.
机译：在医学图像配准过程中，以配准函数（也称相似性度量）为目标函数，以多参数优化方法为获得最佳变换参数的工具。本文利用互信息作为配准函数，分别运用Powell方法和遗传算法对最优变换参数进行探索，并对它们的优化性能进行了评估和比较。实验结果表明，鲍威尔方法可以同时满足单模态和多模态医学图像配准。然而，不幸的是，无论配准精度或运行时间如何，遗传算法都没有被用于医学图像配准，并且需要显着改善。

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