Planning, navigation and monitoring device for CT-guided interventions

所要求的计划、导航和监测设备应连接到计算机断层摄影机，使其能够作为中央信息系统。目前正在与几个工作组联合开展一个项目，以制定方法和算法，促进基于CT的干预措施。其中包括新的基于深度学习的分割技术和路径优化算法，以支持多施源器规划或新的CT图像重建技术，以减少伪影，同时节省辐射剂量。例如，这些用于针尖的基于图像的位置跟踪，从而将附接到机器人臂的超声探头半自动地对准针尖。这使得进一步的基于超声的针导航没有有害的X射线，并有助于改善放射科医生的工作条件。总的来说，目标是开发一种专用的计算机断层扫描仪，该设备针对介入而非诊断进行优化，并且所要求的设备是支持放射科医生进行计划，导航和治疗监测的中央界面。

The requested planning, navigation and monitoring device is to be connected to a computed tomograph in such a way that it can function as a central information system. Methods and algorithms are being developed in a joint project with several working groups to facilitate CT-based interventions. These include new deep-learning-based segmentation techniques and path optimization algorithms to support multi-applicator planning or new CT image reconstruction techniques for artifact reduction while saving radiation doses. These are used, for example, for image-based position tracking of the needle tips and to thus align an ultrasonic probe attached to a robot arm semi-automatically to the needle tip. This allows further ultrasound-based needle navigation without harmful X-rays and contributes to the improvement of working conditions for radiologists.Overall, the aim is to develop a dedicated computed tomograph that is optimized for interventions and not for diagnostics, and for which the requested device is the central interface supporting the radiologists in planning, navigating and therapy monitoring.