虚拟支气管镜检查

G. McLennan, E. Namati, J. Ganatra, M. Suter, E. E. O'Brien, K. Lecamwasam, E. J. R. Van Beek, E. A. Hoffman
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引用次数: 0

摘要

虚拟支气管镜检查正在迅速发展,并逐渐被接受为标准的临床实践。虚拟支气管镜是一个术语,它不仅包括多行探测器x射线计算机断层成像衍生图像,还包括其他计算机图形学和计算机视觉衍生的增值数字图像。用于创建支气管树三维图像渲染的其他成像数据源包括磁共振成像,正电子发射断层扫描,在真实支气管镜下拍摄的数字彩色图像作为宏观光学成像的一部分,以及各种新兴的显微光学成像方式,如基于导管的共聚焦显微镜和光学相干断层扫描。现在存在的软件解决方案可以提供支气管树的简单渲染图,通过它可以添加沿气道中心线的气道腔的透视(这种透视模拟了真正的灵活支气管镜提供给操作员的视图)。这样产生的图像在视觉上是准确的,并且目前可用的软件在分析上也是正确的。更先进的虚拟支气管镜应用,包括基于图像的纵隔和外周肺结构寻路,也在开发中,并正在寻找进入临床研究的途径。由来自多个图像源的图像数据组成的令人兴奋和协同的数据集也正在构建中。一个新出现的问题是加强对这些数据集的理解和报告,这些数据集通常很复杂,并且充满了有用和冗余的信息。eidomics的新学科将为非专业的最终用户提供信息,并采取行动预测重要的结果。这些日益强大的工具将继续推动成像在技术支持的个性化医疗中的应用,以补充基因组学的信息。
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Virtual Bronchoscopy

Virtual bronchoscopy is evolving rapidly, and is becoming accepted into standard clinical practice. Virtual bronchoscopy is a term, which encompasses not only multi-row detector X-ray computerized tomography-derived images, but also other computer graphics and computer vision-derived value-added digital imagery. Other imaging data sources used to create three-dimensional image renderings of the bronchial tree include magnetic resonance imaging, positron emission tomography, the digital colour image taken at real bronchoscopy as part of macro-optical imaging, and various emerging micro-optical imaging modalities, such as catheter-based confocal microscopy and optical coherence tomography. Software solutions now exist for providing simple renderings of the bronchial tree through which a fly-through of the airway lumen along the centreline of the airway can be added (the fly-through mimics the view that a real flexible bronchoscope affords the operator). The images so produced are visually accurate and with currently available software also analytically correct. More advanced virtual bronchoscopic applications, including image-based pathfinding to mediastinal and peripheral lung structures, are also in development, and are finding their way into clinical studies. Exciting and synergistic data sets composed of image data from multiple image sources are also being constructed. One emerging issue is to enhance the understanding and reporting on these data sets, which are often complex, and which are full of useful as well as redundant information. The new discipline of eidomics will inform the non-specialist end user, and act to predict important outcomes. These increasingly powerful tools will continue to advance the use of imaging in technology-supported personalized medicine, to compliment the information from genomics.

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