Wei Yizhi, Huang Bingyu, Zhao Bolin, Lin Zhengyu, Zhou Steven Zhiying
School of Engineering, Huaqiao University, Quanzhou, 362021, China.
College of Design and Engineering, National University of Singapore, Singapore, 117575, Singapore.
Int J Comput Assist Radiol Surg. 2025 Jul 12. doi: 10.1007/s11548-025-03477-z.
Augmented reality (AR) technology holds significant promise for enhancing surgical navigation in needle-based procedures such as biopsies and ablations. However, most existing AR systems rely on patient-specific markers, which disrupt clinical workflows and require time-consuming preoperative calibrations, thereby hindering operational efficiency and precision.
We developed a novel multi-camera AR navigation system that eliminates the need for patient-specific markers by utilizing ceiling-mounted markers mapped to fixed medical imaging devices. A hierarchical optimization framework integrates both marker mapping and multi-camera calibration. Deep learning techniques are employed to enhance marker detection and registration accuracy. Additionally, a vision-based pose compensation method is implemented to mitigate errors caused by patient movement, improving overall positional accuracy.
Validation through phantom experiments and simulated clinical scenarios demonstrated an average puncture accuracy of 3.72 ± 1.21 mm. The system reduced needle placement time by 20 s compared to traditional marker-based methods. It also effectively corrected errors induced by patient movement, with a mean positional error of 0.38 pixels and an angular deviation of 0.51 . These results highlight the system's precision, adaptability, and reliability in realistic surgical conditions.
This marker-free AR guidance system significantly streamlines surgical workflows while enhancing needle navigation accuracy. Its simplicity, cost-effectiveness, and adaptability make it an ideal solution for both high- and low-resource clinical environments, offering the potential for improved precision, reduced procedural time, and better patient outcomes.
增强现实（AR）技术在诸如活检和消融等基于针的手术中，对于提升手术导航具有重大前景。然而，大多数现有的AR系统依赖于患者特异性标记物，这会扰乱临床工作流程，并且需要耗时的术前校准，从而阻碍操作效率和精度。
我们开发了一种新型的多摄像头AR导航系统，该系统通过利用映射到固定医学成像设备的天花板安装标记物，消除了对患者特异性标记物的需求。一个分层优化框架整合了标记物映射和多摄像头校准。采用深度学习技术来提高标记物检测和配准精度。此外，实施了一种基于视觉的姿态补偿方法，以减轻患者移动引起的误差，提高整体定位精度。
通过体模实验和模拟临床场景进行验证，结果表明平均穿刺精度为3.72±1.21毫米。与传统的基于标记物的方法相比，该系统将进针时间减少了20秒。它还有效地校正了由患者移动引起的误差，平均位置误差为0.38像素，角度偏差为0.51°。这些结果突出了该系统在实际手术条件下的精度、适应性和可靠性。
这种无标记AR引导系统在提高针导航精度的同时，显著简化了手术工作流程。其简单性、成本效益和适应性使其成为高资源和低资源临床环境的理想解决方案，具有提高精度、减少手术时间和改善患者预后的潜力。
