Journal of South China University of Technology (Natural Science Edition) ›› 2011, Vol. 39 ›› Issue (2): 125-129,147.doi: 10.3969/j.issn.1000-565X.2011.02.021

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Lung Nodule Recognition Combining Rule-Based Method and SVM

Zhang Jing1  Li Bin1  Tian Lian-fang1  Chen Ping2  Wang Li-fei   

  1. 1. The south China university of technology, automation science and engineering college, guangdong guangzhou 510640; 2. The first affiliated hospital of guangzhou medical college nuclear all-around-doctors, guangdong guangzhou 510120; 3. The blessing of guangzhou university of Chinese traditional medicine hospital image center, guangdong guangzhou 511495
  • Received:2010-03-24 Revised:2010-09-05 Online:2011-02-25 Published:2011-01-02
  • Contact: 李彬(1979-)，男，讲师，博士，主要从事科学计算可视化、图像处理与模式识别研究 E-mail:binleemmboy@yahoo.com.cn
  • About author:张婧(1982-)，女，博士生，主要从事图像处理与模式识别研究
  • Supported by:

    中国博士后科学基金资助项目(20090450866)；广东省教育部产学研结合项目(2o09B09030o057)；教育部高等学校博士学科点专项科研基金资助项目(200805610018)；广东省自然科学基金资助项目(8451064101000631)；广州市番禺区科技攻关项目(2009一z一108—1)；华南理工大学中央高校基本科研业务费资助项目(2009ZM0077)

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Abstract:

In order to effectively recognize lung nodules in CT images,a recognition method combining the rule-based method and the support vector machine（SVM） is proposed to classify the regions of interest（ROIs）.In this method,first,shape features of candidate ROIs are calculated,and some non-nodule regions are filtered out by using the rule-based method.Then,the remaining candidate ROIs are taken as testing and training samples,whose grayscale and texture features are calculated and used as the inputs of SVM to classify the remaining candidate ROIs.Experimental results show that the rule-based method may result in high possibility of misdiagnosis although there is no nodule omission,while the proposed method combining the rule-based method and the SVM is of low possibility of misdiagnosis but of obvious nodule omission.

Key words: image recognition, lung nodule, classifier, support vector machine, rule