北京交通大学学报2017，Vol.41Issue(5)：73-78,6.DOI:10.11860/j.issn.1673-0291.2017.05.011
乳腺X线图像肿块分类方法研究
Research on benign and malignant masses classification in mammogram
摘要
Abstract
The classification of mammographic masses into malignant or benign is one of the important contents in CAD (Computer-Aided Diagnosis) systems.In this paper,mass contour segmentation and mass classification under different features are studied.Based on the idea of maximizing the between-cluster variance of the segmented images,a modified marker controlled watershed segmentation algorithm is proposed and employed to give the coarse segmentation.Then CV (Active Contour without Edge) model is used to refine the coarse segmentation.The classification performance of existing shape features and texture features under different classifiers is tested for the purpose of validating how different features perform in the malignant-benign classification.The proposed method is evaluated on a public database,DDSM (Digital Database for Screening Mammography).The results show that automatic segmentation can get texture features with better classification performances.关键词
信息处理/肿块分类/肿块分割/分水岭算法Key words
information processing/masses classification/masses segmentation/watershed algorithm分类
信息技术与安全科学引用本文复制引用
魏杰,曹旭阳,陈后金,李艳凤..乳腺X线图像肿块分类方法研究[J].北京交通大学学报,2017,41(5):73-78,6.基金项目
国家自然科学基金项目(61502025,61571036) （61502025,61571036）
中国博士后科学基金项目(2015M570029) （2015M570029）
北京交通大学人才基金(2015RC024) （2015RC024）
中央高校基本科研业务费专项资金(2016JBM010)National Natural Science Foundation of China (61502025,61571036) （2016JBM010）
China Postdoctoral Science Foundation(2011M570029) （2011M570029）
Beijing Jiaotong University Talents Foundation(2015RC024) （2015RC024）
Fundamental Research Funds for the Central Universities(2016JBM010) （2016JBM010）
