基于改进头脑风暴优化算法的医学图像配准方法
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上海应用技术大学计算机科学与信息工程学院,上海,201418

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国家自然科学基金(61976140)资助项目;上海应用技术大学协同创新基金(XTCX2019-14)资助项目。


Medical Image Registration Based on Improved Brain Storm Optimization Algorithm
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School of Computer Science & Information Engineering, Shanghai Institute of Technology, Shanghai, 201418, China

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    摘要:

    针对精准医疗中图像配准方法收敛速度慢、精度不够高的问题,提出一种基于改进头脑风暴优化(Improved brain storm optimization, IBSO)算法的医学图像配准方法。配准过程分为3个阶段:首先,将待配准图像进行多分辨率分解;然后,使用IBSO算法对低分辨率图像进行全局粗配准;最后,利用单纯形搜索法对高分辨图像精配准。相比粒子群和单纯形结合算法、差分进化和Powell结合算法,以及头脑风暴和Powell结合算法,在单模态实验中,所提算法平均耗时较以上3种算法分别降低了32.89%、13.91%和13.66%,且最大误差、平均误差最小;在多模态实验中,互信息、归一化互信息、交叉累计剩余熵与归一化互相关指数均优于上述3种配准算法。实验结果表明,所提算法可以有效地提升医学图像配准的精度与速度。

    Abstract:

    Aiming at the problem of slow convergence and low accuracy of image registration method in precision medicine, a registration method based on improved brain storm optimization(IBSO) algorithm is proposed. The new registration includes three steps. Firstly, the unregistered images are decomposed into multi-resolution images. Then, the IBSO algorithm is used for global coarse registration of low-resolution images. Finally, the Simplex is utilized to fine registration of high-resolution images. Compared with methods of particle swarm optimization combined with Simplex, differential evolution algorithm combined with Powell, and brain storm optimization combined with Powell, the average running time of the proposed algorithm reduces by 32.89%, 13.91% and 13.66% respectively in the mono-modality registration experiment, in which the maximum error and the average error are minimum too. It also outperforms the above three registration algorithms in multi-modality registration experiments, in which the measures of mutual information (MI), normalized mutual information (NMI), cross cumulative residual entropy (CCRE) and normalization cross-correlation (NCC) are best in all. Experiments show that the proposed algorithm effectively improves the accuracy and speed of medical image registration.

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曹国刚,朱信玉,陈颖,曹聪,孔德卿.基于改进头脑风暴优化算法的医学图像配准方法[J].数据采集与处理,2020,35(4):730-738

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  • 收稿日期:2020-01-13
  • 最后修改日期:2020-06-22
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  • 在线发布日期: 2020-08-07