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融入空间信息的医学图像优质分割
引用本文:辛学刚,卢振泰,陈武凡.融入空间信息的医学图像优质分割[J].计算机工程与应用,2009,45(34):225-226.
作者姓名:辛学刚  卢振泰  陈武凡
作者单位:南方医科大学生物医学工程学院,广州,510515
基金项目:国家重点基础研究发展规划(973),国家自然科学基金重点项目 
摘    要:传统的FCM分割算法只考虑到图像的灰度信息,而忽略了灰度的空间信息,对于迭加了噪声的图像,难以得到准确的结果。从马尔可夫随机场(MRF)申得到启示,考虑到图像灰度信息及其空间分布出发,提出了一种新的基于邻域(Neighbor)信息FCM分割算法,即NFCM算法。实验结果表明该算法所得到的目标图像的边界特征保持完好,图像边界细腻、连续且定位性能好。

关 键 词:图像分割  马尔可夫随机场  空间信息  模糊聚类算法  NFCM算法
收稿时间:2008-7-7
修稿时间:2008-12-10  

Medical image segmentation incorporate with spatial information
XIN Xue-gang,LU Zhen-tai,CHEN Wu-fan.Medical image segmentation incorporate with spatial information[J].Computer Engineering and Applications,2009,45(34):225-226.
Authors:XIN Xue-gang  LU Zhen-tai  CHEN Wu-fan
Affiliation:School of Biomedical Engineering,Southern Medical University,Guangzhou 510515,China
Abstract:The conventional FCM don’t take into account the spatial information of image and can get the unexpected results of segmentation when dealing with some image contaminated by noise.Inspired by the MRF model,considering the pixel and its neighbor,an improved model is presented to fuzzy C-means algorithm using neighborhood information.The proposed algorithm can reasonably use the spatial information of image and improve the accuracy of segmentation.The results of experiments show that the proposed algorithm can provide powerful image segmentation than many segmentation algorithms.
Keywords:image segmentation  Markov Random Field (MRF)  spatial information  Fuzzy Clustering Method (FCM)  NeighborMarkov Random Field(NFCM)
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