Ophthalmic Surgery Simulation
and Synthetic Data Generation.
and Synthetic Data Generation.
Driven by Machine Learning.
Our Vision
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Our Approach
Synthetic Data Generation
Leverage multimodal AI models for synthetic surgical video data.
Trained on real patient cases.
Featuring a processing pipeline that turns medical imaging data into dynamic and patient-specific simulations.
Anatomy and pathology variations powered by Generative AI trained on diverse patient datasets.
Bridging data gaps for rare and out-of-distribution scenarios.
Surgical Training & Virtual Prototyping
Train and validate AI models in a digital twin environment.
Gain insights into surgical performance and optimize workflows.
Increase acceptance and foster trust in the next generation of surgical systems.
Digital Twin Simulation
Use realistic, patient-specific training environments
that enable data-driven analysis.
stereo microscope
keypoints
semantic annotations
depth maps
Team
Michael
Sommersperger
Sommersperger
Computer Graphics and Machine Learning
Shervin
Dehghani
Dehghani
Computer Vision and Machine Learning
Mathias
Großschädl
Großschädl
Bussiness Development
Dr. Koorosh
Faridpooya
Faridpooya
Medical Advisor
Prof. Dr. Nassir
Navab
Navab
Medical Imaging and Machine Learning Advisor
Prof. Dr. Ali
Nasseri
Nasseri
Medical Robotics Advisor
Julia
Lex
Lex
Bussiness Development
Timon
Sommer
Sommer
Development and Design
Soroush
Fazeli
Fazeli
Machine Learning and Quality Assurance
Featured Publications
Associations
