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首页> 外文会议>Conference on Physiology and Function: Methods, Systems, and Applications Feb 16-18, 2003 San Diego, California, USA >Toward Reliable Multi-Generational Analysis of Anatomical Trees in 3D High-Resolution CT Images
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Toward Reliable Multi-Generational Analysis of Anatomical Trees in 3D High-Resolution CT Images

机译：对3D高分辨率CT图像中的解剖树进行可靠的多代分析

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摘要

Modern micro-CT and multidetector helical CT scanners can produce high-resolution 3D digital images of various anatomical tree structures, such as the coronary or hepatic vasculature and the airway tree. The sheer size and complexity of these trees make it essentially impossible to define them interactively. Automatic approaches, using techniques such as image segmentation, thinning, and centerline definition, have been proposed for a few specific problems. None of these approaches, however, can guarantee extracting geometrically accurate multigenerational tree structures. This limits their utility for detailed quantitative analysis of a tree. This paper proposes an approach for accurately defining 3D trees depicted in large 3D CT images. Our approach utilizes a three-stage analysis paradigm: (1) Apply an automated technique to make a "first cut'' at defining the tree. (2) Analyze the automatically defined tree to identify possible errors. (3) Use a series of interactive tools to examine and correct each of the identified errors. At the end of this analysis, in principle, a more useful tree will be defined. Our paper will present a preliminary description of this paradigm and give some early results with 3D micro-CT images.
机译：现代的微型CT和多探测器螺旋CT扫描仪可以生成各种解剖树结构（例如冠状或肝血管系统和气道树）的高分辨率3D数字图像。这些树的绝对大小和复杂性使得根本不可能以交互方式定义它们。针对一些特定问题，已经提出了使用诸如图像分割，细化和中心线定义等技术的自动方法。但是，这些方法均不能保证提取几何上精确的多代树结构。这限制了它们用于详细定量分析树木的效用。本文提出了一种精确定义大型3D CT图像中描绘的3D树的方法。我们的方法采用三阶段分析范式：（1）应用自动化技术在定义树时进行“第一个切割”；（2）分析自动定义的树以识别可能的错误；（3）使用一系列交互式工具来检查和纠正每个已识别的错误。在分析结束时，原则上，将定义一个更有用的树。我们的论文将提供这种范例的初步描述并提供3D micro-CT的一些早期结果图片。

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