Robust Oral Localization Based on Multicamera Tracking of Self-Identifying Markers
Yaoqing Hu, Mingzhu Zhu, Shaoan Wang, Dongyue Li, Yan Mei Meng, Fusong Yuan, Jinyan Shao, Junzhi Yu · IEEE Transactions on Instrumentation and Measurement · 2024
Oral localization is widely used in oral and maxillofacial surgery. Most existing navigation systems adopt stereo optical devices to track fiducial markers for oral localization. However, they still suffer from line-of-sight occlusion and field-of-view limitation. This paper presents a robust oral localization system that utilizes multi-camera tracking of self-identifying markers to address the above issue. A customized oral clip with self-identifying markers on its curved surface is designed, which is firmly fixed within the patient’s oral cavity. Before surgery, an accurate method based on intraoral scanning is developed to register the patient’s oral cavity with the markers, of which the registration error is less than 0.1 mm. Secondly, a cylindrical marker is applied for calibrating the converging multi-camera system to avoid the blurry sight problem. During surgery, a multi-camera tracking method, integrating nonlinear optimization and an extended Kalman filter, is proposed to localize the oral cavity. We establish a simulated environment to test the accuracy and robustness of the tracking method. Additionally, we set up a real platform using a phantom oral cavity to validate the feasibility of each proposed method. Results reveal that our system yields a closer trajectory (0.37 mm) to the ground truth than that of and a stereo-camera tracking system (1.58 mm), and exhibits a certain robustness against camera occlusion.