Registration of Multi-Resolution Medical Images Using a Modified Artificial Fish-Swarm Algorithm Combined with Powell's Method

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Registration of Multi-Resolution Medical Images Using a Modified Artificial Fish-Swarm Algorithm Combined with Powell's Method

更新时间：2025-07-09

- Registration of Multi-Resolution Medical Images Using a Modified Artificial Fish-Swarm Algorithm Combined with Powell's Method
- Vol. 45, Issue 4, Pages: 46-52(2011)
- 作者机构：
  
  安徽大学计算智能与信号处理教育部重点实验室,合肥,230039
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.41
- Online First：10 April 2011，
  
  Published：2011
- 稿件说明：
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Registration of Multi-Resolution Medical Images Using a Modified Artificial Fish-Swarm Algorithm Combined with Powell's Method[J]. 2011, 45(4): 46-52.
DOI：

Registration of Multi-Resolution Medical Images Using a Modified Artificial Fish-Swarm Algorithm Combined with Powell's Method[J]. 2011, 45(4): 46-52. DOI：

摘要

针对目前基于互信息图像配准的局部极值问题

提出了一种改进的人工鱼群算法和Powell算法结合的多分辨率医学图像配准算法.该算法采用新的相似性测度方法即归一化模糊加权互信息和归一化局部能量加权匹配度

利用多分辨率策略采用HPV插值

并采用改进的人工鱼群算法结合Powell算法完成医学图像的配准.采用改进的人工鱼群算法在图像的最低分辨率上进行全局优化

以全局最优值为初始值

结合Powell算法完成图像配准.这不仅基本解决了互信息函数和Powell算法的局部极值问题

还减少了数据的处理量

加快了配准速度.实验结果表明

文中算法与其他经典的配准算法相比

提高了配准的精确度和性能.

Abstract

A registration algorithm of multi-resolution medical images is proposed by using a modified artificial fish-swarm algorithm combined with Powell's method to address the local maxima of mutual information-based image registration. Fuzzy weighted normalized mutual information and normalized partial energy-weighted matching are proposed as new similarity measures

multi-resolution strategy and HPV interpolation are used

and global optimization is performed with the proposed registration algorithm. Experimental results and comparisons with some existing registration methods in multi-mode medical image registration show that the proposed algorithm improves registration accuracy and performance.

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references

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