Augmented Reality (AR) has been used to facilitate surgical guidance during External Ventricular Drain (EVD) surgery, reducing the risks of misplacement in manual operations. During this procedure, the key challenge is accurately estimating the spatial relationship between pre-operative images and actual patient anatomy in AR environment. This research proposes a novel framework utilizing Time of Flight (ToF) depth sensors integrated in commercially available AR Head Mounted Devices (HMD) for precise EVD surgical guidance. As previous studies have proven depth errors for ToF sensors, we first assessed their properties on AR-HMDs. Subsequently, a depth error model and patient-specific parameter identification method are introduced for accurate surface information. A tracking pipeline combining retro-reflective markers and point clouds is then proposed for accurate head tracking. The head surface is reconstructed using depth data for spatial registration, avoiding fixing tracking targets rigidly on the patient's skull. Firstly, $7.580\pm 1.488 mm$ depth value error was revealed on human skin, indicating the significance of depth correction. Our results showed that the error was reduced by over $85\%$ using proposed depth correction method on head phantoms in different materials. Meanwhile, the head surface reconstructed with corrected depth data achieved sub-millimetre accuracy. An experiment on sheep head revealed $0.79 mm$ reconstruction error. Furthermore, a user study was conducted for the performance in simulated EVD surgery, where five surgeons performed nine k-wire injections on a head phantom with virtual guidance. Results of this study revealed $2.09 \pm 0.16 mm$ translational accuracy and $2.97\pm 0.91$ degree orientational accuracy.

翻译：增强现实（AR）已被用于辅助脑室外引流（EVD）手术中的手术导航，可降低人工操作中因定位偏差引起的风险。在此过程中，关键挑战在于准确估计AR环境中术前影像与实际患者解剖结构之间的空间关系。本研究提出了一种新型框架，利用商用AR头戴式设备（HMD）中集成的飞行时间（ToF）深度传感器实现精确的EVD手术导航。鉴于先前研究已证实ToF传感器存在深度误差，我们首先评估了其在AR-HMD上的特性。随后，引入了一种深度误差模型和患者特异性参数识别方法，用于获取准确的表面信息。进一步提出了一种结合逆向反射标记与点云的追踪管线，以实现精确的头部追踪。基于深度数据重建头部表面用于空间配准，避免了将追踪目标刚性固定在患者颅骨上的问题。结果显示：人类皮肤上的深度值误差为$7.580\pm 1.488 mm$，表明深度校正的重要性。采用所提出的深度校正方法后，不同材料头部模型上的误差降低超过$85\%$。同时，基于校正后深度数据重建的头部表面达到亚毫米级精度。在羊头实验中，重建误差为$0.79 mm$。此外，在模拟EVD手术中开展了用户研究：五名外科医生在虚拟导航下对头部模型进行了九次克氏针穿刺操作，结果显示平移精度为$2.09 \pm 0.16 mm$，角度精度为$2.97\pm 0.91$度。