Surgical Tool Segmentation

Surgical tool segmentation aims to automatically identify and delineate surgical instruments within images or videos, facilitating improved surgical training, skill assessment, and robotic assistance. Current research emphasizes leveraging foundation models like Segment Anything Model 2 for zero-shot segmentation, exploring weakly-supervised and semi-supervised learning techniques to address the scarcity of labeled data, and developing multi-task learning approaches that integrate segmentation with action recognition. These advancements hold significant promise for enhancing the objectivity and efficiency of surgical procedures and accelerating the development of computer-assisted surgical systems.