A New Lung Segmentation Algorithm for Pathological CT Images

摘要：

This paper presents a new lung segmentation algorithm which is based on anatomical knowledge and Snake model. This algorithm totally overcomes the disadvantage of traditional lung segmentation algorithms, which are mainly based on edge extraction, mathematical morphology, region growing, threshold, etc, and cant get satisfied results when segmenting pathological clinical CT images with traditional algorithms. Experiments showed that no matter whether the CT images are pathological or not, this segmentation algorithm has good results, high speed, and total automation.

作者: Lu Meng Hong Zhao

作者单位: School of Information&Engineering Northeastern University Shenyang 110004, P.R.China The Software Center Northeastern University

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 847-850

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）