Imagine a high-tech GPS for brain surgeons that doesn't just show the map, but highlights exactly where the tumor ends and healthy tissue begins in real-time. It uses special light imaging and AI to act like a smart assistant during the operation. This helps doctors remove the cancer more accurately without accidentally damaging healthy parts of the brain.
Neurosurgeons struggle to identify exact tumor margins and face 'brain-shift' that makes navigation inaccurate. Additionally, waiting up to 45 minutes for pathology results slows down surgeries and increases patient risk.
A 3D decision support tool and point-of-care computing system. It uses AI to process multimodal data, including hyperspectral imaging, for real-time surgical guidance.
If you are a surgical navigation provider dealing with the 'brain-shift' phenomenon that ruins map accuracy during surgery — this project developed a 3D decision support tool that integrates multimodal data and AI to maintain precision. This allows for a higher degree of tumor resection while minimizing neurological deficits.
If you are a computing developer dealing with slow intraoperative pathology consultations that can take up to 45 min — this project developed an energy-efficient point-of-care computing system. This reduces surgery time and optimizes the use of hospital resources.
If you are an imaging company dealing with the difficulty of differentiating tumor margins in gliomas — this project developed a system integrating hyperspectral imaging and AI. This increases diagnostic accuracy during the operation to improve patient quality of life.
Based on available project data, specific pricing is not mentioned, but the project aims to improve the cost- and energy-efficiency of neurosurgical workflows.
The project aims to reach TRL7 and includes a roadmap to TRL9, indicating a clear path toward industrial scale and market readiness.
Based on available project data, specific licensing terms are not provided, but the project includes the preparation of a preliminary business plan.
The project runs from 2023-12-01 to 2028-11-30, including a two-year clinical study in 3 clinical sites.
It is designed as a point-of-care computing tool that integrates multimodal data from several independent devices into a 3D decision support tool.
The consortium is composed of 13 partners across 6 countries, showing a strong European reach. It has a balanced mix of 5 universities and 4 research organizations, supported by 2 industry SMEs, resulting in a 15% industry ratio. This structure suggests a heavy emphasis on R&D with a clear transition path toward commercialization via the SMEs.
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Contact us to connect with the STRATUM consortium for TRL7 prototype licensing.
