关键词: 肺裂, 快速行进, 测地线投票, 直方图, 回溯

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 undulating 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 proposed. 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.

Key words: pulmonary fissure, fast marching, geodesic voting, histogram, back-tracing