概括
这项研究引入了一种快速的纤维形状感知方法,使用双层长短期记忆 (LSTM) 网络来准确可视化和导航外科仪器. 这种方法以最小的错误实现实时性能,增强了微创手术.
科学领域:
- 医疗工程 医学工程
- 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:
- 微创手术需要精确的可视化和导航仪器在狭窄的空间.
- 传统方法由于电磁干扰和电离辐射而面临局限性.
研究的目的:
- 开发一种快速而准确的纤维形状感应方法,用于手术仪器导航.
- 克服现有的导航技术的局限性.
主要方法:
- 使用双层长短期内存 (LSTM) 网络进行形状重建.
- 从纤维布拉格格 (FBG) 直接回归的3D坐标波长转移,绕过曲率估计.
- 实现实时推断,具有较低的端到端延迟.
主要成果:
- 实现了实时推断,每秒32,延迟7.3毫秒.
- 显示平均尖端误差为2.9毫米 (0.72%的传感长度).
- 经过验证的高速和高精度纤维形状重建.
结论:
- 提出的基于LSTM的方法为实时光纤形状传感提供了可行的解决方案.
- 这项技术在微创手术中增强实时导航的巨大潜力.
- 该方法解决了手术仪器跟踪的关键挑战.
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