Russian Scientists Build AI Tool That Compresses Days of Cell Analysis Into Minutes

In a leap forward for regenerative medicine, researchers at ITMO University in Russia have developed Cellpose+, an AI-powered platform that drastically accelerates the design of next-gen medical materials—from implants to drug delivery systems

Traditionally, analyzing cellular structures took days of manual labor, as scientists slogged through hundreds of microscopy images. Cellpose+ changes the game: using machine learning, it processes the same data in mere minutes, automatically detecting cell shape, size, density, and nucleus positioning with high precision.

“This used to require multiple apps—or worse, manual work,” said Pavel Zun, project lead and associate professor at ITMO. “Now it’s a single, automated workflow that researchers can monitor and refine, with minimal error.”

Already in trials for biodegradable polymers used in implants, Cellpose+ has the potential to scale far beyond materials science. Future versions could assist in tumor diagnostics, anomaly detection, and cell division research—essentially becoming a digital microscope with built-in insight.

In true open science fashion, Cellpose+ is free and open-source, allowing global researchers to adapt and expand on the work of the Russian team.

By compressing timelines and boosting accuracy, Cellpose+ doesn’t just accelerate research—it gives Russia a sharper edge in the race for AI-powered biomedicine.