One-Step Auto-Registration using Linear Structured Light-based for Neurosurgical Navigation

Neurosurgical navigation system plays a very important role in current neurosurgery. Manual marker-based surgical registration methods provide great accuracy, but involve time-consuming and complex operations that can only be performed prior to sterilization. Neurosurgical navigation system requires a simplified registration process that decreases the difficulty for the surgeon, shortens patient-to-image registration time, and adapts to higher sterile surgical environments. Therefore, this study reports a new contactless automated registration approach using line structured light technology in neurosurgical navigation. The contactless facial point cloud data is acquired by scanning the patient with line structured light. The CT model performs spatial pose enumeration in which all the poses are traversed to find the best of them to match with the facial point cloud, thus realizing one-step automatic registration. Experiments have demonstrated that the average root mean square error is 0.6027 +/- 0.0453 mm for 0.05 relative sampling length, 120 degrees step size, and 200 iterations. One-step registration offers more convenience, simplicity, accuracy and speed over manual registration. In the future, we will strive for spatial iterative algorithm execution speed enhancement and the integration of this registration technique with augmented reality (AR) to establish the relationship between image space, surgical space, and video streaming space.