基于纹理特征和支持向量机的磁共振脑图像组织分类

摘要

Magnetic resonance imaging(MRI)of brain is one of the important means of medical diagnosis. The tissue clas-sification of the magnetic resonance brain images is studied mainly in this paper. The classification is based on the texture fea-tures of the MRI brain tissue. In the process of the experiment,high degree of distinction characteristic values was used to com-pose the feature vector,which was input into support vector machines(SVM)and was classified by the improved SVM. Better classification result can be obtained under the conditions of optimizing the feature vector data and the parameters of SVM.%磁共振脑图像的是医学诊断中的一种重要的手段，在此主要研究磁共振脑图像的组织分类。分类以脑图像各组织的纹理特征为依据。在试验过程中采用区分度较高的特征值，组成特征向量，作为支持向量机的输入，用改进的支持向量机进行分类。在特征向量数据优化和支持向量机参数寻优的条件下，可以取得较好的分类效果。