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Development of an Artificial Intelligence-Based Support Technology for Urethral and Ureteral Stricture Surgery
Sung-Jong Eun1, Jong Mok Park2, Khae-Hawn Kim2
1Digital Health Industry Team, National IT Industry Promotion Agency, Jincheon, Korea.
International Neurourology Journal
|April 4, 2022
Summary
This study introduces an AI system using ResNet-50 to precisely locate urethral strictures during surgery. The technology enhances surgical efficiency by accurately guiding operators to the stenosis area.
Area of Science:
- Urology
- Medical Imaging
- Artificial Intelligence
Background:
- Urethral and ureteral strictures pose surgical challenges.
- Accurate localization of stenosis is critical for effective endoscopic surgery.
Purpose of the Study:
- To develop an AI-powered system for precise stenosis recognition during endoscopic surgery.
- To enhance surgical efficiency in treating urethral and ureteral strictures.
Main Methods:
- Implementation of the ResNet-50 algorithm for image analysis.
- Intraoperative analysis of endoscopic images to detect stenosis location.
- Utilizing AI for real-time clinical guidance to the operator.
Main Results:
- The AI system demonstrated high recognition accuracy for stenosis.
- An average sensitivity of 0.96 confirmed the system's reliable positive identification of true stenosis.
- The system effectively guided surgeons to the precise stenosis area.
Conclusions:
- The ResNet-50 based AI system successfully aids in endoscopic surgery for strictures.
- Accurate stenosis detection and intraoperative guidance improve surgical outcomes.
- Future work will focus on defining conservative and flexible stricture boundaries.
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