东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2008, Vol. 29 ›› Issue (7): 965-967+975.DOI: -

• 论著 • 上一篇    下一篇

基于CT图像的自动肺实质分割方法

贾同;孟琭;赵大哲;王旭;   

  1. 东北大学信息科学与工程学院;东北大学信息科学与工程学院;东北大学信息科学与工程学院;东北大学信息科学与工程学院 辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2008-07-15 发布日期:2013-06-22
  • 通讯作者: Jia, T.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60671050)

Automatic lung parenchyma segmentation on CT image

Jia, Tong (1); Meng, Lu (1); Zhao, Da-Zhe (1); Wang, Xu (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2008-07-15 Published:2013-06-22
  • Contact: Jia, T.
  • About author:-
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摘要： 在肺癌、肺气肿等肺部疾病计算机辅助诊断方法中,肺实质分割是最核心的步骤.提出一种基于三维CT图像序列的新的自动肺实质分割方法,综合利用了阈值分割、区域增长及数学形态学等算法,并在特定体层通过图搜索算法精确定位左右肺前后连接线狭窄区域,有效解决了肺实质边缘结节易分割遗漏及左右肺分离的难题.通过多组胸部CT序列图像的实验证明,该方法对于肺实质分割非常精确有效.

关键词: 计算机辅助诊断, 图像分割, 肺结节检测, 肺实质分割, CT图像

Abstract: The automatic segmentation of lung parenchyma is one of the key techniques to the computer-aided diagnosis (CAD) system for lung cancer, emphysema and other lung diseases. A new automatic lung segmentation based on the 3-D CT image series is proposed integrating the adaptive gray-level threshold, region growing and math morphological algorithms together. And the graph search algorithm is used at specified layers to position accurately the narrow zone formed by the anterior and posterior lines connecting the left and right lung, thus overcoming efficiently the difficulties that the nodules at lung edge are easy to be missed and how to separate the left lung from right one. The experimental results of many sets of CT images verified that the technique proposed is highly exact and efficient for lung parenchyma segmentation.

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