| 基于PSO_KFCM的医学图像分割 |
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| 引用本文： | 裴振奎,胡萍萍.基于PSO_KFCM的医学图像分割[J].计算机工程与设计,2008,29(9):2295-2297. |
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| 作者姓名： | 裴振奎 胡萍萍 |
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| 作者单位： | 中国石油大学(华东)计算机与通信工程学院,山东,青岛,266555 |
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| 摘 要： | 在核模糊聚类算法(KFCM)的基础上,提出了一种新的PSO KFCM聚类算法.新算法利用高斯核函数,把输入空间的样本映射到高维特征空间,利用微粒群算法的全局搜索、快速收敛的特点,代替KFCM算法逐次迭代的过程,在特征空间中进行聚类,克服了KFCM对初始值和噪声数据敏感、易陷入局部最优的缺点.通过对医学图像进行分割,仿真实验结果表明,新算法在性能上比KFCM聚类算法有较大改进,具有更好的聚类效果,且算法能够很快地收敛.
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| 关 键 词： | 微粒群算法 核函数 图像分割 模糊C_均值聚类 特征空间 |
| 文章编号： | 1000-7024(2008)09-2295-02 |
| 修稿时间： | 2007年5月11日 |
Image segmentation based on particle swarm optimization and kernel fuzzy C-means clustering |
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| PEI Zhen-kui,HU Ping-ping.Image segmentation based on particle swarm optimization and kernel fuzzy C-means clustering[J].Computer Engineering and Design,2008,29(9):2295-2297. |
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| Authors: | PEI Zhen-kui HU Ping-ping |
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| Affiliation: | PEI Zhen-kui,HU Ping-ping(College of Computer , Communication Engineering,China University of Petroleum(East China),Qingdao 266555,China) |
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| Abstract: | A novel kernel fuzzy C_means clustering algorithm which uses the merits of the global optimizing and higher convergent speed of particle swarm optimization(PSO) algorithm and combines with kernel fuzzy C_Means(KFCM) is proposed with application to medical image segmentation.The algorithm eliminates FCM trapped local optimum,being sensitive to initial data and the noise data.The performance of this modified KFCM is compared with KFCM.Numerical results of this comparative study are performed on medical images... |
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| Keywords: | particle swarm optimization kernel function image segmentation kernel fuzzy C_means clustering feature space |
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