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为了更安全的机器人辅助手术:一个无标记的增强现实框架.

Ziyang Chen1, Laura Cruciani1, Ke Fan1

  • 1Politecnico di Milano, Department of Electronics, Information and Bioengineering, Milano, 20133, Italy.

Neural networks : the official journal of the International Neural Network Society
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这项研究引入了一个无标记增强现实 (AR) 框架,用于机器人辅助手术. 该AR系统通过防止仪器与关键血管之间的碰撞,从而降低手术内出血的风险,提高了手术安全性.

关键词:
达芬奇的研究工具包无标记增强现实无标记增强现实机器人辅助手术是一种机器人辅助的手术.分段化 分段化 分段化 分段化立体声重建的重建

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科学领域:

  • 医疗机器人 医疗机器人
  • 手术导航 手术导航
  • 增强现实是一种增强现实.

背景情况:

  • 机器人辅助手术 (RAS) 正在发展,增强现实 (AR) 提供了改善外科医生可视化的潜力.
  • 仪器与血管碰撞造成的手术期间出血是RAS的一个重大风险.

研究的目的:

  • 开发和评估一个无标记AR框架,以提高RAS的安全性.
  • 为了防止手术仪器与敏感血管之间的碰撞,从而降低出血风险.

主要方法:

  • 针对3D血管重建的先进立体重建和细分网络的比较.
  • 用操作前模型注册重建的船只.
  • 实施仪器和血管之间的最小距离检测.
  • 在达芬奇研究工具包上与人类实验对象进行机器人辅助淋巴切除术的模拟.

主要成果:

  • 拟议的AR框架有效地引导用户避免与血管碰撞.
  • 用户没有引入任何显著的额外认知负载.
  • 该系统在模拟的外科环境中展示了可用性.

结论:

  • 无标记AR框架通过防止仪器与血管碰撞,成功提高了机器人辅助手术的安全性.
  • 这种灵活的框架将AR集成到医疗机器人平台中,以提高外科安全.