Surgical Instrument Segmentation

Surgical instrument segmentation aims to automatically identify and delineate surgical tools within endoscopic or laparoscopic video footage, crucial for improving minimally invasive surgery. Current research emphasizes improving segmentation accuracy and robustness using various deep learning architectures, including transformers, encoder-decoder networks, and those incorporating temporal and stereo information from video sequences, often leveraging techniques like optical flow analysis and multi-modal fusion (e.g., audio cues). These advancements are driven by the need for more reliable computer-assisted interventions, enabling improved surgical precision, automation, and training. Ultimately, accurate and efficient surgical instrument segmentation promises to enhance surgical safety and outcomes.