Surgical Tool

Automatic recognition and tracking of surgical tools in video is a crucial area of research aiming to improve surgical workflow analysis and training. Current efforts focus on developing robust deep learning models, often incorporating techniques like Hidden Markov Models to account for temporal dependencies in video data and leveraging multi-camera systems to mitigate occlusions. These advancements are driven by the need for large, accurately annotated datasets and improved algorithms that can handle the challenges of similar-looking tools and complex surgical scenes, ultimately leading to more efficient and effective surgical procedures.