Robotic Assisted Imaging

现代外科治疗的范例是通过使用小锁眼进入体内来减少手术的侵入性创伤。机器人辅助系统提供远程操作的仪器，通过提高人体工程学，灵巧性和控制手动锁孔手术仪器的精度，促进微创手术。机器人手术现在在微创前列腺癌和肾癌手术中很常见。但是，体内成像目前受到接入端口的限制，只能提供可见器官表面的信息，这通常不足以在解剖结构中轻松定位，并避免对健康组织的无意损害。该项目将开发机器人辅助成像，利用机器人平台提供的自主性和驱动能力，优化当前外科成像模式可以获得的图像。在机器人辅助手术的背景下，先进的成像技术可以帮助外科医生更安全、更有效地进行手术，通过识别需要保留的结构，同时指导外科医生找到需要切除的解剖目标。提供更好的成像和与机器人系统的集成将通过确保安全、准确的手术操作来改善结果，从而为患者带来多重好处。为了实现这一功能，需要新的理论、计算、控制算法和实时实现来支持动态环境中成像和机器人系统的集成。成像传感器观察到的信息需要反馈到机器人控制回路中，以指导传感器的自动定位和运动，从而保持传感器与运动器官和结构的对齐。目前在机器人辅助手术中，这种程度的自动化在很大程度上是未被探索的，因为它涉及视觉推断、重建和跟踪方面的多重挑战；传感器和各种机器人运动学策略的标定和再标定；与外科工作流程和用户研究的集成。结合术前计划的使用，机器人辅助成像可以根据不同的临床需求做出预先计划的成像选择。除了在外科手术中的直接应用外，机器人辅助成像范例也将适用于许多其他由机器人技术转变的领域，例如制造或检查，特别是在非刚性环境中工作时。为了实现这种跨部门的影响，该项目将建立深厚的理论和强大的软件平台，这些平台非常适合基础奖学金的支持。

The paradigm of modern surgical treatment is to reduce the invasive trauma of procedures by using small keyhole ports to enter the body. Robotic assistant systems provide tele-manipulated instruments that facilitate minimally invasive surgery by improving the ergonomics, dexterity and precision of controlling manual keyhole surgery instruments. Robotic surgery is now common for minimally invasive prostate and renal cancer procedures. But imaging inside the body is currently restricted by the access port and only provides information at visible organ surfaces which is often insufficient for easy localisation within the anatomy and avoiding inadvertent damage to healthy tissues. This project will develop robotic assisted imaging which will exploit the autonomy and actuation capabilities provided by robotic platforms, to optimise the images that can be acquired by current surgical imaging modalities. In the context of robotic assisted surgery, now an established surgical discipline, advanced imaging can help the surgeon to operate more safely and efficiently by allowing the identification of structures that need to be preserved while guiding the surgeon to anatomical targets that need to be removed. Providing better imaging and integration with the robotic system will result in multiple patient benefits by ensuring safe, accurate surgical actions that lead to improved outcomes.To expose this functionality, new theory, computing, control algorithms and real-time implementations are needed to underpin the integration of imaging and robotic systems within dynamic environments. Information observed by the imaging sensor needs to feed back into the robotic control loop to guide automatic sensor positioning and movement that maintains the alignment of the sensor to moving organs and structures. This level of automation is largely unexplored in robotic assisted surgery at present because it involves multiple challenges in visual inference, reconstruction and tracking; calibration and re-calibration of sensors and various robot kinematic strategies; integration with surgical workflow and user studies. Combined with the use of pre-procedural planning, robotic assisted imaging can lead to pre-planned imaging choices that are motivated by different clinical needs. As well as having direct applications in surgery, the robotic assisted imaging paradigm will be applicable to many other sectors transformed by robotics, for example manufacturing or inspection, especially when working within non-rigid environments. For this cross sector impact to be achieved the project will build the deep theoretical and robust software platforms that are ideally suited for foundational fellowship support.