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相关实验视频

Updated: May 6, 2026

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视觉指导手术导航使用计算机视觉进行动态手术内成像更新

Jeremy Ruthberg1, Nicole Gunderson2, Pengcheng Chen2

  • 1Department of Otolaryngology-Head and Neck Surgery, University of Washington, Seattle, Washington, USA.

International forum of allergy & rhinology
|August 23, 2025
PubMed
概括

这项研究引入了一种使用神经辐射场 (NeRF) 创建实时3D手术场重建的新方法,从而提高了内镜手术 (ESS) 的准确性. 这项技术可实现动态手术内成像,以提高手术完整性.

关键词:
三维重建人工智能慢性鼻炎计算机辅助手术深度学习图像指导的手术

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科学领域:

  • 医学成像
  • 计算机视觉
  • 手术技术

背景情况:

  • 在内镜手术 (ESS) 后的残留疾病导致不良结果和重复手术.
  • 目前的图像指导手术系统缺乏动态的手术内更新.
  • 建议使用神经辐射场 (NeRF) 进行手术内CT更新的无传感器视频方法.

研究的目的:

  • 开发和验证使用NeRF进行动态手术内CT更新的新方法.
  • 与手术前CT扫描相比,评估NeRF生成的3D外科现场重建的准确性.
  • 评估这项技术在ESS中提高外科完整性的潜力.

主要方法:

  • 在3D打印模型上进行双边ESS.
  • 用自定义的NeRF管道处理内镜视频进行3D重建.
  • 使用Hausdorff距离,DSC和BAA,将NeRF重建与手术前的CT扫描共同记录,并生成更新的CT模型并与手术后的CT进行比较.

主要成果:

  • 通过0.27 ± 0.076 mm的平均豪斯多夫距离实现了亚毫米表面对齐.
  • 通过0.93±0.012的子相似系数 (DSC) 证明了极好的体积重叠.
  • 布兰德-阿尔特曼分析显示了可接受的体积协议,平均差异为0.40cm3.

结论:

  • 计算机视觉,特别是NeRF,可以通过内镜视频进行准确,动态的CT更新,而不需要外部跟踪.
  • 这种软件驱动的工具可视化切除的进展,有可能提高ESS手术的完整性.
  • 这项技术为下一代外科导航平台提供了途径.