Intrathoracic airway trees: Segmentation and airway morphology analysis from low-dose CT scans
Intrathoracic airway trees: Segmentation and airway morphology analysis from low-dose CT scans
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DOI：
10.1109/tmi.2005.857654
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发表时间：
2005-12-01
影响因子：
10.6
通讯作者：
Sonka, M
中科院分区：
文献类型：
--
作者：
Tschirren, J;Hoffman, EA;Sonka, M
从体积计算机断层扫描(CT)图像中分割人体呼吸道树为许多临床应用和生理学研究奠定了重要的一步。以前提出的算法存在一个或几个问题：泄漏到周围的肺实质，需要用户手动调整参数，运行时间过长。针对低剂量CT扫描在肺部筛查研究中的应用日益广泛的问题，提出了一种基于模糊连通性的低剂量CT肺部分割方法。当呼吸道分支被分段时，使用跟随其的小的自适应感兴趣区域。这有几个好处。该算法能够及早发现并避免泄漏，分割算法能够自动适应图像参数的变化，计算时间保持在适中的范围内。新方法是稳健的，因为它适用于各种类型的扫描(低剂量和常规剂量，正常受试者和患病受试者)，而不需要用户手动调整任何参数。与常用的区域生长分割算法的比较表明，新的方法检索到的气道分支数量明显更多。提出了一种对气道进行准确的横断面气道测量的方法作为附加处理步骤。测量是在原始灰度级体积中进行的。在体模上的验证表明，对于所有的气道大小和气道方向，亚体素都达到了精度。
The segmentation of the human airway tree from volumetric computed tomography (CT) images builds an important step for many clinical applications and for physiological studies. Previously proposed algorithms suffer from one or several problems: leaking into the surrounding lung parenchyma, the need for the user to manually adjust parameters, excessive runtime. Low-dose CT scans are increasingly utilized in lung screening studies, but segmenting them with traditional airway segmentation algorithms often yields less than satisfying results.In this paper, a new airway segmentation method based on fuzzy connectivity is presented. Small adaptive regions of interest are used that follow the airway branches as they are segmented. This has several advantages. It makes it possible to detect leaks early and avoid them, the segmentation algorithm can automatically adapt to changing image parameters, and the computing time is kept within moderate values. The new method is robust in the sense that it works on various types of scans (low-dose and regular dose, normal subjects and diseased subjects) without the need for the user to manually adjust any parameters. Comparison with a commonly used region-grow segmentation algorithm shows that the newly proposed method retrieves a significantly higher count of airway branches.A method that conducts accurate cross-sectional airway measurements on airways is presented as an additional processing step. Measurements are conducted in the original gray-level volume. Validation on a phantom shows that subvoxel accuracy is achieved for all airway sizes and airway orientations.