Aykac Deniz, Hoffman Eric A, McLennan Geoffrey, Reinhardt Joseph M
Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA.
IEEE Trans Med Imaging. 2003 Aug;22(8):940-50. doi: 10.1109/TMI.2003.815905.
The lungs exchange air with the external environment via the pulmonary airways. Computed tomography (CT) scanning can be used to obtain detailed images of the pulmonary anatomy, including the airways. These images have been used to measure airway geometry, study airway reactivity, and guide surgical interventions. Prior to these applications, airway segmentation can be used to identify the airway lumen in the CT images. Airway tree segmentation can be performed manually by an image analyst, but the complexity of the tree makes manual segmentation tedious and extremely time-consuming. We describe a fully automatic technique for segmenting the airway tree in three-dimensional (3-D) CT images of the thorax. We use grayscale morphological reconstruction to identify candidate airways on CT slices and then reconstruct a connected 3-D airway tree. After segmentation, we estimate airway branchpoints based on connectivity changes in the reconstructed tree. Compared to manual analysis on 3-mm-thick electron-beam CT images, the automatic approach has an overall airway branch detection sensitivity of approximately 73%.
肺通过肺气道与外部环境进行气体交换。计算机断层扫描（CT）可用于获取肺部解剖结构的详细图像，包括气道。这些图像已被用于测量气道几何形状、研究气道反应性以及指导手术干预。在进行这些应用之前，气道分割可用于识别CT图像中的气道管腔。气道树分割可由图像分析师手动完成，但树状结构的复杂性使得手动分割既繁琐又极其耗时。我们描述了一种在胸部三维（3-D）CT图像中分割气道树的全自动技术。我们使用灰度形态学重建来识别CT切片上的候选气道，然后重建一个连通的三维气道树。分割后，我们根据重建树中的连通性变化估计气道分支点。与对3毫米厚的电子束CT图像进行手动分析相比，自动方法对气道分支的总体检测灵敏度约为73%。
