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Creation of 4D Imaging Data using Open Source Image Registration Software

机译:使用开源图像注册软件创建4D图像数据

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摘要

4D images (3 spatial dimensions plus time) using CT or MRI will play a key role in radiation medicine as techniques for respiratory motion compensation become more widely available. Advance knowledge of the motion of a tumor and its surrounding anatomy will allow the creation of highly conformal dose distributions in organs such as the lung, liver, and pancreas. However, many of the current investigations into 4D imaging rely on synchronizing the image acquisition with an external respiratory signal such as skin motion, tidal flow, or lung volume, which typically requires specialized hardware and modifications to the scanner. We propose a novel method for 4D image acquisition that does not require any specific gating equipment and is based solely on open source image registration algorithms. Specifically, we use the Insight Toolkit (ITK) to compute the normalized mutual information (NMI) between images taken at different times and use that value as an index of respiratory phase. This method has the advantages of (1) being able to be implemented without any hardware modification to the scanner, and (2) basing the respiratory phase on changes in internal anatomy rather than external signal. We have demonstrated the capabilities of this method with CT fluoroscopy data acquired from a swine model.
机译:随着呼吸运动补偿技术的广泛应用,使用CT或MRI的4D图像(3个空间尺寸加上时间)将在放射医学中发挥关键作用。对肿瘤及其周围解剖结构的运动的预先了解将允许在诸如肺,肝和胰腺的器官中产生高度共形的剂量分布。但是,当前对4D成像的许多研究都依赖于将图像采集与外部呼吸信号(例如皮肤运动,潮气或肺体积)同步,这通常需要专门的硬件和对扫描仪的修改。我们提出了一种新颖的4D图像采集方法,该方法不需要任何特定的选通设备,并且仅基于开源图像配准算法。具体来说,我们使用Insight工具包(ITK)计算在不同时间拍摄的图像之间的标准化互信息(NMI),并将该值用作呼吸相位的指标。该方法的优点是:(1)无需对扫描仪进行任何硬件修改即可实现;(2)呼吸阶段基于内部解剖结构而不是外部信号的变化。我们已经从猪模型获取的CT透视数据中证明了该方法的功能。

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