使用可语言提示的数字孪生实现机器人X射线设备的智能控制
Intelligent Control of Robotic X-ray Devices using a Language-promptable Digital Twin
AI总结：
该研究提出基于语言可提示数字孪生的机器人X射线智能控制系统，通过语言对齐的X射线分割基础模型更新患者数字孪生，实现多自主功能，尸体实验验证了其高成功率与精准定位能力。
摘要：
自然语言为控制机器人C臂X射线系统提供了便捷灵活的接口，让高级功能和控制操作更易使用。然而，搭建语言接口需要专门的AI模型来解析X射线图像，生成可供推理的语义表征，而这类AI模型的固定输出限制了语言控制的功能范围。引入可通过语言提示、与语言对齐的灵活AI模型，能为各类任务和操作流程提供更通用的接口。\n本系统采用与语言对齐的X射线图像分割基础模型，基于对目标解剖结构的稀疏重建，持续更新患者数字孪生（patient digital twin）。该系统支持可视化、患者特异性视图查找、新视角自动准直等自主功能，可响应“聚焦下腰椎”这类指令。\n在一项尸体研究中，用户通过语音指令完成躯干各处结构的可视化、定位和准直操作，端到端成功率达84%。对随机朝向图像的事后分析显示，本研究的患者数字孪生可将35种常见请求结构的定位误差控制在51.68毫米以内，可从任意朝向完成定位与隔离。\n研究结果表明，智能机器人X射线系统可直接融合医生表达的操作意图。尽管当前术中X射线分析基础模型存在失效模式，但随着模型性能提升，它们将助力打造高度灵活的智能机器人C臂。
英文摘要：
Natural language offers a convenient, flexible interface for controlling robotic C-arm X-ray systems, making advanced functionality and controls accessible. However, enabling language interfaces requires specialized AI models that interpret X-ray images to create a semantic representation for reasoning. The fixed outputs of such AI models limit the functionality of language controls. Incorporating flexible, language-aligned AI models prompted through language enables more versatile interfaces for diverse tasks and procedures. Using a language-aligned foundation model for X-ray image segmentation, our system continually updates a patient digital twin based on sparse reconstructions of desired anatomical structures. This supports autonomous capabilities such as visualization, patient-specific viewfinding, and automatic collimation from novel viewpoints, enabling commands 'Focus in on the lower lumbar vertebrae.' In a cadaver study, users visualized, localized, and collimated structures across the torso using verbal commands, achieving 84% end-to-end success. Post hoc analysis of randomly oriented images showed our patient digital twin could localize 35 commonly requested structures to within 51.68 mm, enabling localization and isolation from arbitrary orientations. Our results demonstrate how intelligent robotic X-ray systems can incorporate physicians' expressed intent directly. While existing foundation models for intra-operative X-ray analysis exhibit failure modes, as they improve, they can facilitate highly flexible, intelligent robotic C-arms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
