Robot Assisted

Robot-assisted surgery is rapidly advancing, driven by efforts to improve precision, efficiency, and safety. Current research focuses on developing computer vision techniques, such as transformer-based object detection and segmentation models, to enable robots to accurately identify anatomical landmarks and surgical instruments during procedures like prostatectomy and intubation. These advancements leverage both real-world and simulated datasets to overcome data limitations and improve model robustness, ultimately aiming for autonomous or semi-autonomous surgical assistance. The resulting improvements in image guidance and surgical workflow have significant implications for minimally invasive surgery and patient outcomes.