东北大学学报:自然科学版 ›› 2018, Vol. 39 ›› Issue (7): 942-948.DOI: 10.12068/j.issn.1005-3026.2018.07.007

• 信息与控制 • 上一篇    下一篇

一种基于ARG的肺结节良恶性度判定方法

赵海, 杨婷婷, 朱宏博, 窦圣昶   

  1. (东北大学 计算机科学与工程学院, 辽宁 沈阳110169)
  • 收稿日期:2017-02-27 修回日期:2017-02-27 出版日期:2018-07-15 发布日期:2018-07-11
  • 通讯作者: 赵海
  • 作者简介:赵海(1959-),男,辽宁沈阳人,东北大学教授,博士生导师.冯明杰(1971-), 男, 河南禹州人, 东北大学副教授; 王恩刚(1962-), 男, 辽宁沈阳人, 东北大学教授,博士生导师.
  • 基金资助:
    辽宁省科学技术计划项目(2015401039); 辽宁省教育厅重点实验室基金资助项目(LZ2014015).国家自然科学基金资助项目(51171041).

Method of Measuring the Benign and Malignancy of Pulmonary Nodules Based on ARG

ZHAO Hai, YANG Ting-ting, ZHU Hong-bo, DOU Sheng-chang   

  1. School of Computer Science & Engineering, Northeastern University, Shenyang 110169, China.
  • Received:2017-02-27 Revised:2017-02-27 Online:2018-07-15 Published:2018-07-11
  • Contact: YANG Ting-ting
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摘要: 基于CT影像的肺结节的良恶性识别是肺癌诊断的重要环节,针对这一问题,提出一种基于属性关系图(attributed relational graph, ARG)的肺结节良恶性度判定方法.该方法以肺结节CT图像块作为输入,利用ARG构建其特征结构,并从大量ARGs中挖掘与或图(and-or graph, AoG)作为肺结节类别识别模板,即肺结节良恶性度判定的依据.此外,为提高模板挖掘效率,该方法利用马尔可夫毯(Markov blanket, MB)发现算法去除图像中的冗余特征,降低ARG节点数量.实验结果表明,该方法对恶性肺结节的识别率达到90.12%,能够帮助正确、快速辨识与分析肺结节良恶性,具有一定的实用价值.

关键词: ARG, 与或图, 马尔可夫毯, 肺结节, 良恶性

Abstract: Identification of benign and malignant pulmonary nodules is an important task during the diagnosis of lung cancer. Aimed for solving this problem, a method of measuring the malignancy of pulmonary nodules based on the attributed relational graph (ARG) was proposed. Feature structures of input lung nodule CT image patches were constructed with ARGs and the nodule category template was built by mining and-or graph (AoG) from ARGs in the proposed method. Moreover, Markov blanket discovering algorithm was applied for discriminative features selection to reduce the node number of ARGs, so the computational complexity of the graph matching for AoG mining was greatly reduced. Experimental results show that the recognition rate of malignant pulmonary nodules is up to 90.12%, thus the proposed method can help identify the benign and malignant pulmonary nodules accurately and rapidly.

Key words: ARG (attributed relational graph), and-or graph, Markov blanket, pulmonary nodule, benign and malignant

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