形式从功能:基于向量场的方法来分析血管树的CT图像

J. Williams, L. B. Wolff
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引用次数: 2

摘要

我们从血管树的x射线计算机断层扫描(CT)体积图像中提取拓扑和局部结构信息,并以促进生理模型创建的形式呈现。生理学家将血管树建模为一个连接的管道网络,迄今为止,产生这种模型的唯一准确数据来自解剖和测量。到目前为止,在活的有机体中对树的动态行为进行建模是不可能的。从CT扫描中建立模型将增加生理学和诊断研究中可用信息的数量和质量。提出了一种高效、准确的管网体图像分析技术。通过局部操作,将体图像转换为类似于理想流体流过管网的矢量场。该字段提供了将图像的显著特征浓缩成增广欧几里得最小生成树(EMST)的信息。这种增强的emst被证明是血管树的信息丰富和逻辑抽象表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Form from function: a vector field based approach to the analysis of CT images of the vascular tree
We extract topological and local structural information from x-ray computed tomography (CT) volume images of the vascular tree and present it in a form that facilitates creation of physiological models. Physiologists model the vascular tree as a connected network of tubes and, to date, the only accurate data available to produce such models has come from dissection and measurement. Modeling the dynamic behavior of the tree in a living organism has been, until now, impossible. Building models from CT scans will increase the volume and quality of informution available for both the study of physiology and diagnosis. We present an efJicient, accurate analysis technique for volume images of tube networks. Using local operations, the volume image is transformed into a vectorfield which resembles idealized fluid flow through the tube network. This field provides information to condense the salient features of the image into an augmented Euclidean minimum spanning tree (EMST). This augmented EMSTproves to be an information-rich and logical abstract representation of the vascular tree.
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