摘要
支持向量机被看作是对传统分类器的一个好的替代,特别是在高维数据空间下,具有较好的泛化能力。本文首次采用支持向量机方法对医学图像进行了分类研究。为了检验该分类方法的有效性与稳健性,对不同的噪声图像进行试验,试验结果表明,即使存在噪声的情况下,支持向量机方法也能获得较好的分类结果。
The Support Vector Machine (SVM) approach is considered a good candidate because of its high generalization performance, even when the dimension of the feature space is very high. This paper firstly investigates the application of support vector machines for medical image classification. In order to verify the effectiveness and robustness of the proposed classification system, we make brain tissues classification for different noise corrupted images. Experimental results demonstrate the effectiveness of SVMs in brain tissues classification.
出处
《信号处理》
CSCD
2004年第2期208-212,共5页
Journal of Signal Processing
