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首页> 美国卫生研究院文献>Computational and Mathematical Methods in Medicine >A Semiautomatic Segmentation Algorithm for Extracting the Complete Structure of Acini from Synchrotron Micro-CT Images
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A Semiautomatic Segmentation Algorithm for Extracting the Complete Structure of Acini from Synchrotron Micro-CT Images

机译：一种半同步分割算法用于从同步加速微CT图像中提取Acini的完整结构

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摘要

Pulmonary acinus is the largest airway unit provided with alveoli where blood/gas exchange takes place. Understanding the complete structure of acinus is necessary to measure the pathway of gas exchange and to simulate various mechanical phenomena in the lungs. The usual manual segmentation of a complete acinus structure from their experimentally obtained images is difficult and extremely time-consuming, which hampers the statistical analysis. In this study, we develop a semiautomatic segmentation algorithm for extracting the complete structure of acinus from synchrotron micro-CT images of the closed chest of mouse lungs. The algorithm uses a combination of conventional binary image processing techniques based on the multiscale and hierarchical nature of lung structures. Specifically, larger structures are removed, while smaller structures are isolated from the image by repeatedly applying erosion and dilation operators in order, adjusting the parameter referencing to previously obtained morphometric data. A cluster of isolated acini belonging to the same terminal bronchiole is obtained without floating voxels. The extracted acinar models above 98% agree well with those extracted manually. The run time is drastically shortened compared with manual methods. These findings suggest that our method may be useful for taking samples used in the statistical analysis of acinus.
机译：肺腺泡是最大的气道单位，带有肺泡，可以进行血液/气体交换。必须了解腺泡的完整结构，才能测量气体交换的路径并模拟肺部的各种机械现象。从其实验获得的图像中通常手动分割完整的腺泡结构是困难且非常耗时的，这妨碍了统计分析。在这项研究中，我们开发了一种半自动分割算法，用于从小鼠肺部闭合胸部的同步加速微CT图像中提取腺泡的完整结构。该算法结合了基于肺结构的多尺度和分级性质的常规二进制图像处理技术。具体地，去除较大的结构，同时通过依次依次施加腐蚀和膨胀算子，参考先前获得的形态计量数据来调整参数，来从图像中分离出较小的结构。在没有漂浮体素的情况下，获得了属于同一末端细支气管的孤立腺泡簇。提取的98％以上的腺泡模型与手动提取的模型非常吻合。与手动方法相比，运行时间大大缩短。这些发现表明我们的方法对于采集用于腺泡统计分析的样品可能有用。

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