Hypervision, a spin-out company from King’s College London that aims to advance computer-assisted tissue analysis for improved surgical precision and patient safety, has signed a strategic development agreement with imec. The collaboration targets the co-development of scalable technologies tailored for surgical applications, as the company works to scale its on-chip hyperspectral imaging and real-time AI analytics. Hypervision's technology delivers tissue-level insights, including on oxygenation, perfusion, and tissue differentiation. Its regulatory-cleared intraoperative imaging platform combines on-chip hyperspectral imaging with real-time AI analytics operating at over 60 fps. Additionally, the technology is designed to integrate into existing surgical vision platforms and workflows. The company's platform is currently under clinical evaluation in U.K. hospitals, with a primary focus on gastrointestinal surgery. Though hyperspectral imaging is already used in medical applications, previous hyperspectral systems have struggled with integration due to hardware complexity, slow processing speeds, and poor compatibility with surgical workflows. These bottlenecks can restrict the use of these system to research settings or post-operative analysis. Hypervision’s technology simultaneously delivers conventional color imagery and real-time quantitative tissue oxygenation maps, extending the surgeon’s visual capability beyond the limits of human vision. This dual-modality view has the potential to make surgical procedures more informed, precise, and safe. Images were captured in a laparoscopic pre-clinical setting with induced ischemia of the large bowel. StO2: Tissue oxygen saturation. Courtesy of imec. As part of the collaboration, imec is leveraging its expertise in semiconductor fabrication, equipment, and process technology to develop on-chip spectral imaging and to design and manufacture interference-based optical filters at the wafer level. imec's CMOS infrastructure provides compact, clean, and high-yield optical filter integration with scalability to high-volume production at low cost.