Tool Tracking

Tool tracking in surgical videos aims to automatically identify and follow the movements of surgical instruments, enabling improved computer-assisted surgery and surgical skill assessment. Current research focuses on developing robust algorithms, often employing deep learning architectures like YOLO and transformers, to address challenges such as tool occlusion, variations in camera views, and the need for accurate tool re-identification. These advancements are crucial for creating more reliable surgical robots, providing real-time feedback during procedures, and automating the time-consuming process of surgical skill evaluation. The ultimate goal is to enhance surgical precision, safety, and training.