计算机科学 ›› 2014, Vol. 41 ›› Issue (5): 304-307.doi: 10.11896/j.issn.1002-137X.2014.05.065
张翡,范虹,郝艳荣
ZHANG Fei,FAN Hong and HAO Yan-rong
摘要： 针对FCM算法分割医学MR图像存在的运算速度慢、对初始值敏感以及难以处理MR图像中固有Rician噪声等缺陷,提出了一种结合非局部均值的快速FCM算法。该算法的核心是首先针对MR图像中存在的Rician噪声,利用非局部均值算法对图像进行去噪处理,消除噪声对分割结果的影响；然后根据所提出的新的自动获取聚类中心的规则得到初始聚类中心；最后将得到的聚类中心作为快速FCM算法的初始聚类中心用于去噪后的图像分割,解决了随机选择初始聚类中心造成的搜索速度慢和容易陷入局部极值的问题。实验表明,该算法能够快速有效地分割图像,并且具有较好的抗噪能力。
| [1] Gudbjartsson H,Patz S.The Rician distribution of noisy MRI data [J].Magnetic Resonance in Medicine,1995,4(6):910-914 [2] Dunn J C．A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters[J]．Journal of Cybernetics,1973,3(3):32-57 [3] 李志梅,肖贵德.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,2009,5(12):187-189 [4] Sikka K,Sinha N,Singh P K,et al.A fully automated algorithm under modified FCM framework for improved brain MR image segmentation[J]．Magnetic Resonance Imaging,2009,27:994-1004 [5] 张慧哲,王坚.基于初始聚类中心选取的改进FCM聚类算法[J].计算机科学,2009,6(6):206-209 [6] Chen Song-can,Zhang Dao-qiang．Robust image segmentation using FCM with spatial constraint based on new kernel-induced distance measure[J]．IEEE Transactions on Systems Man and Cybernetics,2004,34(4):1907-1916 (下转第314页)(上接第307页) [7] 林亚忠,郝刚.利用邻域差异性信息的FCM改进算法[J].计算机应用,2011,1(2):375-378 [8] 依玉峰,高立群.基于全局空间相似性的模糊聚类算法[J].东北大学学报:自然科学版,2012,3(2):178-181 [9] Liu Y L,Wang J,Chen X,et al．A robust and fast non-localmeans algorithm for image denoising[J].Journal of Computer Science and Technology,2008,23(2):270-179 [10] Bezedek J C．Cluster validity with fuzzy sets[J].Cybernetics and Systems,1973,3(3):58-73 [11] Bezedek J C．Mathematical methods for systematic and taxonomy[C]∥Proceedings of Eight International Conference on Numerical Taxonomy．San Franciso,1975 [12] Xie X L,Beni G A.Validity measure for fuzzy clustering[J].IEEE Trans Pattern Anal Mach Intell,1991,3:841-846 |
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