An improved FCM medical image segmentation algorithm based on MMTD.
An improved FCM medical image segmentation algorithm based on MMTD.
复制标题
一种改进的基于MMTD的FCM医学图像分割算法
DOI：
10.1155/2014/690349
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发表时间：
2014
影响因子：
--
通讯作者：
Zhang S
中科院分区：
文献类型：
--
作者：
Zhou N;Yang T;Zhang S
图像分割在医学图像处理中占有重要地位。模糊c-均值(FCM)是医学图像分割中常用的聚类算法之一。但由于在图像分割中没有考虑图像的空间信息，模糊C均值算法对噪声非常敏感。介绍了一种用于图像分割中模糊信息处理的中介数学系统。该方法建立了基于媒体真实度(MMTD)的媒体相似度度量，并利用像素点与邻域的相关性来定义媒体隶属函数。提出了一种改进的基于MMTD的FCM医学图像分割算法，该算法考虑了医学图像的一些空间特征。实验结果表明，该算法比标准的FCM算法具有更强的抗噪能力、更强的确定性和更少的模糊性。这将使其在医学图像分割中得到实用和有效的应用。
Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM) is one of the popular clustering algorithms for medical image segmentation. But FCM is highly vulnerable to noise due to not considering the spatial information in image segmentation. This paper introduces medium mathematics system which is employed to process fuzzy information for image segmentation. It establishes the medium similarity measure based on the measure of medium truth degree (MMTD) and uses the correlation of the pixel and its neighbors to define the medium membership function. An improved FCM medical image segmentation algorithm based on MMTD which takes some spatial features into account is proposed in this paper. The experimental results show that the proposed algorithm is more antinoise than the standard FCM, with more certainty and less fuzziness. This will lead to its practicable and effective applications in medical image segmentation.