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FIRE: an open-software suite for real-time 2D/3D image registration for image guided radiotherapy research

机译:FIRE:用于实时2D / 3D图像配准的开放软件套件,用于图像指导的放射治疗研究

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Radiotherapy treatments have changed at a tremendously rapid pace. Dose delivered to the tumor has escalated while organs at risk (OARs) are better spared. The impact of moving tumors during dose delivery has become higher due to very steep dose gradients. Intra-fractional tumor motion has to be managed adequately to reduce errors in dose delivery. For tumors with large motion such as tumors in the lung, tracking is an approach that can reduce position uncertainty. Tumor tracking approaches range from purely image intensity based techniques to motion estimation based on surrogate tracking. Research efforts are often based on custom designed software platforms which take too much time and effort to develop. To address this challenge we have developed an open software platform especially focusing on tumor motion management. FIRE is a freely available open-source software platform. The core method for tumor tracking is purely intensity based 2D/3D registration. The platform is written in C++ using the Qt framework for the user interface. The performance critical methods are implemented on the graphics processor using the CUDA extension. One registration can be as fast as 90ms (11Hz). This is suitable to track tumors moving due to respiration (~0.3Hz) or heartbeat (~1Hz). Apart from focusing on high performance, the platform is designed to be flexible and easy to use. Current use cases range from tracking feasibility studies, patient positioning and method validation. Such a framework has the potential of enabling the research community to rapidly perform patient studies or try new methods.
机译:放射疗法的治疗已经以非常快的速度发生了变化。运送至肿瘤的剂量已逐渐增加,而有风险的器官(OARs)得到更好的保存。由于非常陡峭的剂量梯度,在剂量输送过程中移动的肿瘤的影响变得更高。分数内肿瘤运动必须得到适当管理,以减少剂量输送中的错误。对于运动较大的肿瘤(例如肺部肿瘤),跟踪是一种可以减少位置不确定性的方法。肿瘤跟踪方法的范围从纯粹基于图像强度的技术到基于替代跟踪的运动估计。研究工作通常基于定制设计的软件平台,这需要花费大量时间和精力进行开发。为了应对这一挑战,我们开发了一个开放的软件平台,重点关注肿瘤运动管理。 FIRE是免费提供的开源软件平台。肿瘤追踪的核心方法是纯粹基于强度的2D / 3D配准。该平台是使用Qt框架的用户界面以C ++编写的。关键性能方法是使用CUDA扩展在图形处理器上实现的。一次注册的速度可以高达90ms(11Hz)。这适用于跟踪由于呼吸(〜0.3Hz)或心跳(〜1Hz)而移动的肿瘤。除了专注于高性能之外,该平台还被设计为灵活且易于使用。当前的用例范围包括跟踪可行性研究,患者定位和方法验证。这样的框架具有使研究界能够迅速进行患者研究或尝试新方法的潜力。

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