KARL STORZ Advances AI-based Quality Analysis in Surgery

Technological breakthrough: AI-supported image analysis

At the heart of the project is a software for analyzing endoscopic image data from minimally invasive procedures, such as laparoscopy, for which a first functional prototype was presented in recent weeks. “The solution is based on advanced deep learning methods and enables precise analysis of surgical skills—from hand stability and instrument guidance to surgical phase recognition and response to intraoperative challenges such as blood and smoke,” said Dr. Lars Mündermann, Director of Digital Health Technology at KARL STORZ. In addition, the software considers efficiency metrics such as time spent, redundant movements, and periods of inactivity. The data obtained can be used by surgeons to continuously improve the quality of their surgery. This objective assessment is based on AI models that have been trained on extensive, manually annotated video data. 

From research to the operating room: Integration into the OR1 platform 

The research results could be integrated into KARL STORZ's OR1^™ platform in the long term. With over 12,000 operating rooms installed worldwide, there is great potential to support surgical quality assurance digitally on a global scale. The software would be able to analyze surgical procedures retrospectively or in real time, thus contributing to the continuous improvement of clinical processes. In Germany alone, over 16 million operations are performed annually.* Studies show that the experience of surgeons in particular has a direct influence on postoperative risk. Until now, quality assessment has mostly been done manually—for example, using paper forms or manual video analysis. The new AI-based solution creates an automated, standardized, and scalable alternative for the first time. Professor Martin Wagner from Dresden University Hospital said: “AI-supported quality analysis is a crucial step toward making surgical skills measurable and accessible—for every clinic and every team worldwide.”  

Next steps: Validation and clinical piloting 

The software will be further trained, validated, and tested in clinical pilot environments throughout 2026. At the same time, a network of leading university hospitals is being established to serve as pioneers of AI-based quality measurement and ensure the robustness of the solutions. The software architecture will meet the high requirements for data protection, interoperability, and clinical integration. “With the SurgicalAIHubGermany project, KARL STORZ is making a groundbreaking contribution to the digital transformation of surgery,” said Christy Gaudet, Global Head of Solutions at KARL STORZ. “The combination of technological innovation, clinical relevance, and globally scalable infrastructure makes this project a milestone – for research, practice, and patient safety.”

Press Contact: