基于CT图像的肺气管树3D分割方法的研究

目的:对肺部气管树的分割在临床上具有重要应用价值。针对目前肺气管树分割存在的问题,本文提出了一种结合区域生长和形态学方法的气管树3D分割的方法。方法:首先,采用基于3D联通区域与形态学的方法分割出CT序列图像中的肺实质;其次,利用3D区域生长法初步提取气管树;然后,利用形态学分割方法选取细小气管候选区域,并与上一步分割结果合成三维肺气管区域;最后,再次利用区域生长法去除伪气管区域,提取出最终的气管树。结果:实验结果表明,三维区域生长方法能够很好地获得气管/主支气管、段气管及主要的气管分支,而形态学方法能够有效地检测出细小气管区域。所以利用本文方法可以简单、有效地提取出肺气管树,并防止区域生长过程中的遗漏现象。结论:本文方法可为肺部气管的定量分析奠定基础,具有十分重要的临床诊断意义。

Three-dimensional Pulmonary Airway Tree Segmentation from CT Images

Objective: Pulmonary airway tree segmentation is very valuable in clinic application.Aiming at solving segmentation problems presently,a three-dimensional segmentation method for extracting pulmonary airway tree from CT images is proposed in this paper.Methods: Firstly,the lung parenchyma was obtained from CT images using a three-dimensional(3D) segmentation method.Then,the main pulmonary airway was segmented using 3D region growing method.Next,the morphology method was used to segment the small airway regi...