Sung Gon Park, Jeonghyun Park, Hong Rock Choi, Jun Ho Lee, Sung Tae Cho, Young Goo Lee, Hanjong Ahn, Sahyun Pak
BACKGROUND AND OBJECTIVE: Recently, deep learning algorithms, including convolutional neural networks (CNNs), have shown remarkable progress in medical imaging analysis. Semantic segmentation, which segments an unknown image into different parts and objects, has potential applications in robotic surgery in areas where artificial intelligence (AI) can be applied, such as in AI-assisted surgery, surgeon training, and skill assessment. We aimed to investigate the performance of a CNN-based deep learning model in real-time segmentation in robot-assisted radical prostatectomy (RALP)...
April 2024: European urology open science