北京生物医学工程

基于混合优化算法的医学图像配准方法

A medical image registration algorithm based on hybrid optimization algorithm

作者：别术林刘杰唐子淑邱禧荷

单位：北京交通大学生物医学工程系（北京100044）

关键词：互信息；Powell算法；遗传算法

分类号：

出版年·卷·期（页码）：2015·34·3（234-238）

摘要：

基于互信息的图像配准算法计算复杂度高，配准速度慢。针对这一问题，本文提出一种基于改进遗传算法和Powell算法相结合的医学图像配准方法。首先针对传统遗传算法收敛速度慢、易早熟的缺陷，本文对遗传操作中的交叉运算过程提出了改进策略，并将改进的遗传算法与Powell算法相结合，充分利用遗传算法的全局搜索能力与Powell算法的局部搜索能力。与Powell算法和未改进的遗传算法相比，本文提出的算法极大地缩短了图像配准所用的时间,同时提高了算法的抗噪性。

Image registration algorithm based on mutual information has high complexity and low speed. To solve the problem, a new image registration method based on improved genetic algorithm and Powell algorithm is proposed in this paper. Considering the shortages of the standard genetic algorithm, such as prematurity and slow convergence that may result in mismatching, in this paper, we improve the crossover operation of the genetic operations. At the same time, we combine the improved genetic algorithm and Powell algorithm. The method makes full use of the global search capability of genetic algorithm and the local search capability of Powell algorithm. Compared with Powell algorithm and the traditional genetic algorithm, this algorithm we proposed can effectively improve the image registration velocity and noise immunity.

参考文献：

［1］郑莹, 李光耀. 区域和局部信息结合的双向医学图像配准［J］. 中国图象图形学报, 2011,16(1): 90-96.

Zheng Ying，Li Guangyao. Bilateral medical image registration based on regional and local information［J］. Journal of Image and Graphics, 2011,16(1):90-96.

［2］杨金宝, 刘长春, 胡顺波. 广义信息熵在医学图像配准中的应用［J］.计算机工程与应用, 2008,44(8):34-36.

Yang Jinbao, Liu Changchun, Hu Shunbo. Medical image registration based on generalized entropy measures［J］. Computer Engineering and Applications, 2008,44(8):34-36.

［3］Lu G, Yan J. Image registration based on criteria of feature point pair mutual information［J］.IET Image Process,2011,6(5):560-566.

［4］沈小卫, 何明一. 一种基于混合优化算法的医学图像配准方法［J］. 计算机应用研究, 2010,27(8):3159-3161.

Shen Xiaowei, He Mingyi. Medical image registration based on hybrid optimization algorithm［J］. Application Research of Computers, 2010,27(8):3159-3161.

［5］冯雪芳, 吴锡生. 一种混合搜索策略的图像配准方法研究［J］.计算机仿真，2012,29(9):274-277.

Feng Xuefang, Wu Xisheng. Hybrid search optimization strategy of image registration method research［J］. Computer Simulation, 2012,29(9):274-277.

［6］Viola PA, Wells WM. Alignment by Maximization of Mutual Information［C］. Boston, MA：Proc of the 5th Int Conf Computer Vision, 1995:16-23.

［7］Thevenaz P, Unser M. Optimization of mutual information for multiresolution image registration［J］.IEEE Trans Image Processing, 2000,9(12):2083-2099.

［8］Meng FL, Wu SX. Research of genetic algorithm in function optimizer based on HCI［C］//Proceedings of the IEEE International Symposium on IT in Medicine and Education. Piscataway. NJ:IEEE Press, 2008,1:1049-1052.

［9］滕皓, 曹爱增. 一种改进变尺度混沌优化的模糊量子遗传算法［J］.计算机工程, 2010,36(13):175-177.

Teng Hao, Cao Aizeng. A meliorated mutative scale chaos optimization fuzzy quantum genetic algorithm［J］.Computer Engineering,2010, 36(13): 175-177.

［10］周其慧, 宋余庆. 基于多分辨率和Powell算法的医学图像配准［J］. 计算机应用研究, 2013,30(4):1256-1258.

Zhou Qihui, Song Yuqing. Medical image registration based on multi-resolution and Powell algorithm［J］. Application Research of Computers, 2013,30(4):1256-1258.

服务与反馈：

【文章下载】【加入收藏】

提示：您还未登录，请登录！点此登录