We are thrilled to announce that our team’s very first journal paper has been officially published! This research is co-authored by Chloe Shu Hui Ong, Hoi Pong Nicholas Wong, Manchi Leung, Yu-Chieh Lee, Bo-An Tsai, Seu-Hwa Chen, Jeff Shih-Chieh Chueh, and Ho Yee Tiong.
This study demonstrates the pilot use of a deep learning-based computer vision (CV) system to automatically recognize key anatomical structures during laparoscopic donor nephrectomy (LDN). By adapting the advanced YOLO v11x network, the system is capable of accurately and in real-time identifying critical areas, including the spleen, left kidney, renal artery, renal vein, and ureter.
This innovative research not only aims to help prevent intraoperative injuries , but it also represents a crucial first step for future artificial intelligence (AI)-guided applications, such as intra-operative guidance, surgical education, and operative standards evaluation.
[Paper Details]
Paper Title: Utilising artificial intelligence to identify surgical anatomy during laparoscopic donor nephrectomy – a validation and feasibility study
Journal: Scientific Reports (2026)
Authors: Chloe Shu Hui Ong, Hoi Pong Nicholas Wong, Manchi Leung, Yu-Chieh Lee, Bo-An Tsai, Seu-Hwa Chen, Jeff Shih-Chieh Chueh & Ho Yee Tiong
