Real-time AI-based algorithm for ophthalmic surgery

Our team is developing a real-time AI-based computer vision algorithm designed to assist clinicians during high-precision ophthalmic procedures.

The project focuses on advanced image analysis of live surgical imagery, enabling automated detection and visual highlighting of critical anatomical boundaries. The system is built as a software-based decision-support tool that enhances the surgeon’s visual perception while maintaining full clinical control.

Project Objectives

The algorithm is being developed to:

• Process live surgical imagery in real time

• Automatically assess image quality before analysis (focus, illumination, visibility of the region of interest)

• Detect and outline key anatomical structures using AI-based image processing

• Provide visual overlays that support intraoperative decision-making

• Deliver low-latency performance suitable for time-sensitive surgical workflows

Technical Scope

This project is focused entirely on AI and software development. Core technical areas include:

• Computer vision model development for anatomical feature detection

• Image quality validation algorithms

• Real-time processing pipeline optimization

• Visual overlay generation for surgical guidance

• Integration-ready software architecture for use with clinical imaging systems

Innovation Aspects

This work demonstrates our expertise in building AI systems for environments where:

• Visual precision is critical

• Decisions must be supported instantly

• Algorithm reliability and consistency are essential

• AI enhances — but does not replace — the medical professional

By combining real-time image analysis with intelligent visual guidance, the algorithm supports more consistent interpretation of surgical imagery and contributes to improved procedural accuracy.