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首页> 外文期刊>Biomedical Engineering: Applications, Basis and Communications >3D tracheobronchial airway tree segmentation from thorax CT images
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3D tracheobronchial airway tree segmentation from thorax CT images

机译：来自胸部CT图像的3D气管支气管气道树分割

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摘要

Segmentation of the lung structures is an important operation in the medical analysis. This paper is proposing a region growing algorithm for airway segmentation. The proposed method for the airway tree segmentation works fully in 3D and performs the measurements in the original gray-scale volume for increased accuracy and efficiency. This algorithm uses region growing and morphological operators. The airway segmentation algorithm is intended to serve qualitative and quantitative purposes, and additional three descriptors are being used for evaluation of the airway segmentation. The proposed method was evaluated using the database of 15 patients who underwent lung CT scans, with varying image quality and anatomical changes. Overlap measure is used to show the difference between measured volumes from the established gold standard and the proposed method. The student t-test and Pearson test showed high correlation of the results with the gold standard. Overall, the test results were satisfactory since accurate segmentation was achieved in 95% of the patients.
机译：肺部结构的分割是医学分析中的重要操作。本文提出了一种用于气道分割的区域增长算法。所提出的气道树分割方法完全可以在3D中工作，并且可以在原始灰度级中执行测量，以提高准确性和效率。该算法使用区域生长和形态算子。气道分割算法旨在用于定性和定量目的，另外三个描述符用于评估气道分割。使用数据库对15例行肺部CT扫描，图像质量和解剖结构变化的患者进行了评估。重叠量度用于显示根据既定的金标准和所提出的方法测得的体积之间的差异。学生t检验和Pearson检验显示结果与金标准高度相关。总体而言，由于在95％的患者中实现了准确的分割，因此测试结果令人满意。

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