A voxel image-based pulmonary airflow simulation method with an automatic detection algorithm for airway outlets.,International Journal for Numerical Methods in Biomedical Engineering

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A voxel image-based pulmonary airflow simulation method with an automatic detection algorithm for airway outlets.
International Journal for Numerical Methods in Biomedical Engineering ( IF 2.2 ) Pub Date : 2020-01-27 , DOI: 10.1002/cnm.3305
Fei Jiang _{1,

2,

3,

4} , Tsunahiko Hirano ₅ , Junji Ohgi _{1,

2} , Xian Chen _{1,

2}

Affiliation

Investigations of pulmonary airflows in respiratory systems are important for the diagnostics and treatment of pulmonary diseases. For accurate prediction of the flow field in an airway, a numerical simulation must be conducted using the true geometry from computed tomography (CT) data. Flow simulation is still a difficult task because of the mesh generation process and preprocessing setup procedures. In this study, we developed a voxel image‐based simulation method using an automatic detection algorithm for airway outlets to simplify the simulation process and improve its applicability in the medical field. Our approach is based on the lattice Boltzmann method with a topology analysis algorithm, which can preserve all raw information from the original CT images and give an accurate flow field inside the airways. Our method can reproduce the essential flow features inside airways, is highly efficient, and decreases the overall processing time. Thus, it has a great potential for future real‐time airflow analyses to provide airflow information to medical experts.

中文翻译：

基于体素图像的肺气流量模拟方法，具有气道出口自动检测算法。

呼吸系统中肺气流的研究对于肺部疾病的诊断和治疗很重要。为了准确预测气道中的流场，必须使用来自计算机断层扫描（CT）数据的真实几何图形进行数值模拟。由于网格生成过程和预处理设置过程，流模拟仍然是一项艰巨的任务。在这项研究中，我们开发了一种基于自动像素算法的基于体素图像的气道出口模拟方法，以简化模拟过程并提高其在医学领域的适用性。我们的方法基于具有拓扑分析算法的格子Boltzmann方法，该算法可以保留原始CT图像中的所有原始信息，并在气道内提供准确的流场。我们的方法可以重现气道内部的基本流动特征，效率很高，并减少了总体处理时间。因此，它具有用于将来的实时气流分析以向医学专家提供气流信息的巨大潜力。

更新日期：2020-01-27

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