Real-Time AI-Assisted Stone Detection and Segmentation for Robotic Ureterorenoscopy in Kidney Stone Surgery

This project aims to develop and implement a real-time artificial intelligence (AI) system to assist in stone detection and segmentation during robotic ureterorenoscopy (URS) procedures for kidney stone treatment. By integrating advanced AI algorithms into the surgical workflow, the system will identify and localize urinary tract stones with high accuracy, enhancing intraoperative decision-making and surgical precision. The project brings together urologists, engineers, and data scientists to improve clinical outcomes, reduce operative times, and support training in endourology. This innovation has the potential to set new standards in minimally invasive urologic surgery.