Dynamic calibration and multi-view fusion of active vision tracking system for surgical instrument

Abstract In recent years, surgical instrument tracking has gained significant attention in the field of surgical navigation. An often-overlooked problem lies in the instrument’s irregular movement conflicting with the tracking system’s fixed viewpoint, leading to line-of-sight occlusion, marker occlusion, and sub-optimal accuracy. The active vision tracking system (which actively adjusts the camera viewpoint) is applied to address this issue. In this paper, two algorithms of multi-view fusion and dynamic calibration are proposed in multi-camera active vision to allow each camera to adjust its viewpoint independently. These algorithms are integrated into the parallel computing of the frontend and backend to implement the positioning of the instrument from multiple perspectives and real-time calibration of multiple cameras. Simulations and experiments are carried out to test the accuracy and robustness of the proposed tracking system. Results reveal that our system achieves a closer trajectory (0.12 mm) to the ground truth compared to a stereo camera tracking system (0.32 mm). The proposed tracking system can keep track of the instruments within the positioning volume at different surgical phases, ensuring consistent navigation and improving positioning stability and accuracy.