Surgical instrument segmentation is fundamentally important for facilitating cognitive
intelligence in robot-assisted surgery. Although existing methods have achieved accurate …

Deep learning for computer vision can be leveraged for interpreting surgical scenes and
providing surgeons with real-time guidance to avoid complications. However, neither …

Background This study aimed to evaluate the use of artificial intelligence (AI) to detect the
critical view of safety during elective laparoscopic cholecystectomy. Methods This was a …

Self-supervised learning (SSL) has potential for effective representation learning in medical
imaging, but the choice of data augmentation is critical and domain-specific. It remains …

Purpose: Segmentation of surgical scenes may provide valuable information for real-time
guidance and post-operative analysis. However, in some surgical video frames there is …

During laparoscopic cholecystectomy (LC), automatic Calot's triangle region of interest
(CTROI) recognition can assist surgeons enhance the safety and efficiency of surgical …

Artificial intelligence (AI) and machine learning (ML) algorithms show promise in
revolutionizing many aspects of surgical care. ML algorithms may be used to improve …

Background Laparoscopic cholecystectomy (LC) is the gold standard procedure for the
treatment of benign gallbladder diseases, but there is the risk of intraoperative bile duct …

Purpose: Ensuring excellent video quality is crucial for the success of minimally invasive
surgical procedures without disrupting the surgical procedure flow. Real-time laparoscopic …

Real time surgical video semantic segmentation requires accurate per-frame performance,
inter-frame temporal consistency and high inference speeds. Additionally surgical guidance …