天津工业大学学报Issue(1)：59-63,5.
基于小波变换的肝脏CT图像分类
Classification of liver CT images based on wavelet transform
摘要
Abstract
A liver CT image classification method based on wavelet transform was presented. Firstly, wavelet and gray level co-occurrence matrix texture features were extracted. Secondly, Mahalonobis distance separability criterion and genetic algorithms were cornbined for feature selection and optimization. Finally, the support vector machine was used to classify the liver CT images. In this paper, features of two kind wavelets and extraction methods on the classification were discussed. Also the algorithm was simulated by software. The experiments showed that the liver CT images can be classified effectively by wavelet transform.关键词
肝脏CT图像/小波变换/灰度共生矩阵/支持向量机Key words
liver CT images/wavelet transform/gray level co-occurrence matrix(GLCM)/support vector machine(SVM)分类
信息技术与安全科学引用本文复制引用
韩晓军,赵宇,杨国环..基于小波变换的肝脏CT图像分类[J].天津工业大学学报,2015,(1):59-63,5.基金项目
国家自然科学基金 （）
