Podcast
How do you digitize a blood smear at 100x resolution without the mechanical complexity of traditional high-powered optics? That was the question Scopio Labs was founded to answer.
In this interview with The AI Journal, Scopio CTO and co-founder Erez Naaman traces the path from that question to the Full-Field imaging technology that powers the company’s diagnostic platform today.
Erez explains why hematology morphology remained one of the last manual workflows in the clinical lab – not because no one tried to digitize it, but because of a fundamental limitation in optics. Traditional microscopy forces a choice between resolution and field of view: zoom in enough to see intracellular detail, and you lose the broader context of the sample. Zoom out, and you lose the detail needed for confident clinical decisions.
Scopio’s approach replaces that trade-off with computational photography – capturing raw imaging data and using algorithms to reconstruct a high-resolution, full-field image of the sample. Rather than relying on expensive optics and precise mechanics, the system uses math to compute what a traditional lens cannot deliver: both the full clinical context and the cellular detail in a single digital view.
The conversation also covers how Scopio’s AI-powered Decision Support System shifts the lab professional’s role from manually searching for cells to verifying what the AI has found – and how full digitization enables real-time remote access, replacing the physical transport of glass slides between sites.
Published by The AI Journal. Hosted by Tom Allen.
Event
Thought leadership
Event
Full-Field Cell Morphology
Webinar
Full-Field Cell Morphology
