数据采集与处理2009，Vol.24Issue(6)：734-737,4.
基于Ncut分割和SVM分类器的医学图像分类算法
Ncut-Based Segmentation and SVM Classifier for Medical Image Classification
摘要
Abstract
To identify tumor part on a computer tomography(CT)image,this paper proposes a novel computer aided diagnosis(CAD)scheme based on normalized cut(Ncut)image segmentation and support vector machine(SVM)classifier.Firstly,the Ncut segmentation method is used to perform the segmentation and to obtain the region of interest(ROI).Then,such image features like histogram,gray level co-occurrence matrix to construct the feature space are extracted.Finally,SVM classifier is trained and used to perform the classification.The classification results show that the new scheme can provide useful help for better diagnosis.Thus,the method can solve the problem of medical diagnosis error caused by the human fatigue and the subjective factor.关键词
医学图像/Ncut图像分割/特征提取/分类/计算机辅助诊断(CAD)Key words
medical image classification/Ncut(Normalized cut)/image segmentation/feature extraction/classifier/computer aided diagnosis(CAD)分类
信息技术与安全科学引用本文复制引用
谢红梅,连宇,彭进业..基于Ncut分割和SVM分类器的医学图像分类算法[J].数据采集与处理,2009,24(6):734-737,4.基金项目
西北工业大学毕业设计重点扶持(521030102)资助项目 （521030102）
新世纪优秀人才支持(NCET-07-0693)资助项目. （NCET-07-0693）
