An Artificial Intelligence-Based System for Identifying Ureteral Stricture Regions
The proposed method, which utilizes the YOLOv5 algorithm, can support surgery for patients with ureteral stricture. This system assists surgical procedures by accurately detecting strictures through real-time image analysis. Future research aims to provide both conservative and flexible boundary estimates for determining the stricture location.
Authors
- Jong Mok Park (ORCID: https://orcid.org/0000-0002-4430-7851)
- Khae Hawn Kim (ORCID: https://orcid.org/0000-0002-7045-8004)
Institutions
- Chungnam National University (KR)
Publication Details
- Journal
- International Neurourology Journal
- Published
- 2025-11-26
- DOI
- https://doi.org/10.5213/inj.2550324.162
- Primary Topic
- Ureteral procedures and complications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chungnam National University
- Chungnam National University Hospital