计算机工程与应用2017，Vol.53Issue(24)：191-195,201,6.DOI:10.3778/j.issn.1002-8331.1606-0433
基于测地线投票的CT图像肺裂检测
Detection of pulmonary fissure in CT image based on geodesic voting
摘要
Abstract
Pulmonary fissure detection in CT image plays a key role for early disease examination and later treatment. However, pulmonary fissures in 2D image are soft tissues which appear as thin, weak and varying structures, often undu-lating planar surfaces with blurred boundaries. This is further complicated by presence of surrounding vessels and other structures. To solve these problems, a new regional iteration and back-tracking algorithm based on geodesic voting is pro-posed. The main procedure is as follows:A geodesic distance fieldis constructed with the fast marching method and a histogram peak finding method is used to locate the fissure branch. Then fissure branches are detected iteratively with a regionback-tracking method. The topological structure with fine branches is preserved while the noise is simultaneously suppressed. The experiment results show that the proposed method is less sensitive to noise with a good fault tolerance performance. It also improves the accuracy and computation efficiency of pulmonary fissure detection compared with the conventional global back-tracking methods.关键词
肺裂/快速行进/测地线投票/直方图/回溯Key words
pulmonary fissure/fast marching/geodesic voting/histogram/back-tracing分类
信息技术与安全科学引用本文复制引用
谭高,肖昌炎,文谦..基于测地线投票的CT图像肺裂检测[J].计算机工程与应用,2017,53(24):191-195,201,6.基金项目
国家自然科学基金(No.61172160). （No.61172160）
