用摄像头手势操控手术影像，无需额外设备。
Touchless Intraoperative Image Access System Based on Vision-Based Hand Tracking
- 单个摄像头捕捉手势，实时估计算法
- 延迟低、控制稳定，满足手术流畅需求
- 无需训练或硬件，适合临床快速部署
术中无接触医学图像交互日益重要，需兼顾无菌环境与操作连续性。本文提出一种基于单个RGB相机的视觉手势系统，实现术中影像的无接触导航。系统采用MediaPipe Hands实时进行手部关键点2.5D估计，将简单直观的手势映射为平移、旋转和缩放指令，支持自然连续操作。系统架构独立于可视化软件，本研究中集成至PyVista。通过帧级日志与量化分析评估延迟、稳定性及交互鲁棒性，实验结果表明系统具备实时性能，延迟低且控制稳定，符合流畅交互要求。该方案验证了低成本无接触术中影像访问的可行性，为后续临床评估奠定基础。
原文摘要 · Abstract (English)
Touchless interaction with medical images is becoming increasingly important in the surgical field, where sterility and continuity of the operational workflow are essential requirements. This work presents a vision-based system for intraoperative navigation of medical images through hand gestures acquired using a single RGB camera. Unlike many existing solutions, the system does not require additional hardware or user-specific training. Hand tracking is performed in real time using MediaPipe Hands, which provides a 2.5D estimation of hand landmarks. Simple and intuitive gestures are then mapped into translation, rotation, and zoom commands, enabling continuous and natural interaction with the image viewer. The system architecture is independent from the visualization software and, for implementation simplicity, in this study it was integrated with PyVista. Performance was evaluated through frame-level logging and quantitative analysis of latency, stability, and interaction robustness metrics. Experimental results highlight real-time behavior, with reduced latencies and stable control, in line with the requirements of fluid interaction. The system demonstrates the feasibility of a low-cost touchless solution for intraoperative access to medical images, laying the groundwork for future clinical evaluations.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。