Surgical Navigation

Surgical navigation aims to improve the accuracy and safety of surgical procedures by providing real-time visualization and guidance to surgeons. Current research focuses on developing markerless systems using computer vision techniques, including deep learning models like neural radiance fields (NeRFs) and graph neural networks, to track instruments and reconstruct 3D anatomical models from various image modalities (e.g., fluoroscopy, endoscopy, RGB-D). These advancements leverage techniques such as simultaneous localization and mapping (SLAM), signed distance fields (SDFs), and augmented/mixed reality interfaces to enhance situational awareness and improve surgical precision. The ultimate goal is to reduce invasiveness, improve patient outcomes, and streamline surgical workflows.