摘要
采用CT电影模式扫描获取肺组织切片数据,确定这些切片的时相关系是构建四维肺部模型的关键步骤.针对现有方法存在的不足,根据相邻图像最相似原理,提出一种改进的4D-CT图像排序法.首先基于半自动动阈值法从原始胸腔切片数据中分割出肺组织图像;然后选定基准时相点,并结合均方根误差作为相似性测度确定相邻床位间图像的时相关系;再利用最小二乘曲线拟合消除切片层间距误差;最后实现了肺模型重建.实验结果表明,采用文中方法构建出的各时相点肺模型表面光滑、轮廓清晰,与呼吸运动变化规律相符,验证了该方法的有效性,并为实现肺部模型的动态仿真奠定了基础.
Determining the phase relations between the lung tissue images acquired by means of CT cine scan is a key step to build the 4D lung model. To solve the problems of existing methods, we propose an improved method for sorting 4D-CT images according to the principle that the adjacent images are most similar. Firstly, the lung tissues are segmented from the initial thorax images using the semi- automatic threshold segmentation algorithm. Then, a benchmark phase is selected and the root mean square error is used as the similarity metric to determine the phase relation between the adjacent couches. Following that, the least square fitting is applied to eliminate the slice spacing error between the adjacent couches. Finally, the lung model reconstruction is carried out. The results indicate that the reconstructed lung model of each phase has a smooth surface with a clear outline, and is consistent with the variation of respiratory movements. Therefore, the proposed method is verified to be effective. Moreover, a good foundation has been laid out for the study of dynamic lung modeling and simulation at the next stage.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2014年第12期2155-2162,共8页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60871099)
中央高校基本科研业务费专项基金(CQDXWL-2013-032)
