Deep‐learning segmentation to guide bladder neck recognition in robot‐assisted radical prostatectomy

Key Points

• This research aims to improve anatomical recognition during robotic surgeries to support novice surgeons.
• Developed a deep-learning segmentation model for anatomical structures.
• Evaluated the model's performance in recognizing the bladder neck during surgery.
• Assessed effects on speed and accuracy for novice surgeons.
• The segmentation model significantly improved the recognition speed of anatomical structures.
• Performance enhancements were particularly beneficial for novice surgeons.
• Potential implications for better training in surgical education.