机器人X射线设备的智能控制使用语言提示数字双胞胎
Benjamin D Killeen1, Anushri Suresh2, Catalina Gomez2
1Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, 21218, MD, USA. killeen@jhu.edu.
概括
这项研究引入了一种新的AI系统,用于使用自然语言控制机器人C臂X射线机器. 智能系统提高了医学成像程序的灵活性和准确性.
科学领域:
- 医疗成像医学成像
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
背景情况:
- 自然语言接口为机器人C臂X射线系统提供灵活的控制.
- 目前用于X射线解释的AI模型在实现基于语言的全面控制方面存在局限性.
- 需要先进的AI模型来实现更具适应性和特定任务的机器人C臂功能.
研究的目的:
- 开发和评估一种与语言结合的AI系统,用于控制机器人C臂X射线系统.
- 通过自然语言,使医疗成像设备的交互更加灵活和智能化.
- 克服目前语言控制系统中固定输出AI模型的局限性.
主要方法:
- 利用语言对齐的基础模型进行X射线图像细分.
- 开发了一个系统,根据图像重建,不断更新患者的数字双胞胎.
- 通过语言命令启用了像可视化,查看和结合等自主功能.
主要成果:
- 在对使用者用口头命令控制机器人X射线系统的尸体研究中,实现了84%的端到端成功.
- 患者的数字双胞胎在随机定向图像中精确地定位了51.68±30.84毫米内的35个常见结构.
- 展示了从任意方向定位和隔离对象的能力.
结论:
- 智能机器人X射线系统可以通过先进的AI有效地结合医生的意图.
- 尽管基础模型目前存在局限性,但未来的进步有望实现高度灵活和智能化的机器人C臂.
- 开发的系统显示了在手术内X射线成像中彻底改变控制和功能的潜力.
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