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改进FCM算法在颅脑磁共振图像分割中的应用

Brain MR image segmentation based on modified Fuzzy C-means
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摘要 模糊C均值(FCM)聚类算法广泛应用于医学图像分割中,但该算法在分割低信噪比图像时,会产生较大的偏差。为解决这一问题,本文提出一种改进的FCM算法,充分考虑相邻像素之间的影响,对FCM的目标函数做一定的修改。实验表明,该算法与FCM算法相比,既能有效分割图像,又对低信噪比图像具有很好的分割效果。 Objective Fuzzy c-means is widely used in medical image segmentation,but the algorithm is less ef-fective for image with low SNR.Methods To solve this problem,a modified fuzzy c-means algorithm is proposed in this paper,which the image＇s space information is fully considered.Conclusion The experiments show that,the modified algorithm is effective for the image with low SNR.
作者 王猛 王玉锋 苏蕊
机构地区 济宁医学院信息工程学院
出处 《济宁医学院学报》 2010年第4期291-293,共3页 Journal of Jining Medical University
基金 济宁医学院青年科研基金项目资助
关键词 医学图像分割 模糊聚类 模糊C均值 Medical image segmentation Fuzzy clustering Fuzzy C-Means
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献8

  • 1Bezdek JC. Pattern recognition with fuzzy objective function algorithms[M]. Plenum Press, New York. 1981:278-286.
  • 2Zhang Dao qiang,Chen Song-can. A novel kernelized fuzzy C- means algorithm with application in medical image Segmentation[J]. Artificial Intelligence in Medicine, 2004,32 ( 1 ) :37- 50.
  • 3李志梅,肖德贵.快速模糊C均值聚类的图像分割方法[J].计算机工程与应用,2009,45(12):187-189. 被引量：25
  • 4Pham DI.. Spatial models for fuzzy clustering[J]. Comput Vis Imag Understand, 2001,84 : 285-297.
  • 5Mohamed N, Ahmed MN. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data [J]. IEEE Trans Med Imag,2002,21(3) :193-199.
  • 6Chuang KS, Tzeng HI., Chen S, et al. Fuzzy c means clustering with spatial information for image segmentation [J]. Comput Med Imag Graphics,2006,30:9-15.
  • 7朱泉同,张建伟,陈允杰,孟祥瑞.基于改进的FCM的人脑MR图像分割[J].计算机应用与软件,2008,25(12):235-238. 被引量：3
  • 8Nikhil P R,Bezdek J C. On cluster validity for the fuzzy C - means model[J].IEEE Transactions on Fuzzy Systems, 1995,3(3) :370-379.

二级参考文献21

  • 1Bezdek JC. Pattern recognition with fuzzy objective function algorithms [M]. Plenum Press, New York. 1981.
  • 2Hungmc, Yangdl. An Efficient Fuzzy C-Means Clustering Algorithm[A ]. IEEE International Conference on Data Mining, California, USA, 2001:225- 232.
  • 3Zhang D Q,Chen S C ,Pan Z S,et al. Kernel-based fuzzy clustering incorporating spatial constraints for image segmentation[ A]. Proc. International Conference on Machine Learning and Cybernetics, 2003,4: 2189 -2192.
  • 4Nikhl PR,Bezdek JC. On cluster validity for the fuzzy c-means model [ J ]. IEEE Transactions on Fuzzy Systems, 1995,3 ( 3 ) :370 - 379.
  • 5Start Z Li, Markov Random Field Modeling in Image Analysis [ J ]. Springer,2001, ISBN 4 - 431 - 70309 - 8.
  • 6Dunn J C.A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters[J].J Cybemet,1973,3(3): 32-57.
  • 7Bezdek J C.Pattern recognition with fuzzy objective function algorithms[M].New York : Plenum Press, 1981.
  • 8Jan A K,Murtym N,Flyrm P J.Data clustering:A review[J].ACM Computer Survey, 1999,31(3 ) :264-323.
  • 9Young WonLin,Lee S U.On the color image segmentation algorithm based on the thresh holding and the fuzzy C_means techniques[J].Pattern Recognitions, 1990,23(6) :935-952.
  • 10Ke J.Fast accurate fuzzy clustering through reduced precision[D]. University of South Florida, 1999.

共引文献25

济宁医学院学报
2010年 第4期

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