The digitalisation of microscopy technologies, combined with automated image analysis workflows, has transformed the field by enabling scientists to replace qualitative observations with high-quality quantitative measurements. However, determining which structures, cells or areas of interest to image to obtain relevant biological information remains a key challenge — a fundamental yet complex task. For instance, identifying a ‘representative’ cell demands years of experience and subjective judgement, making the process time-consuming and prone to bias. This highlights the urgent need for innovation in microscopy workflows.

Microscopy core facilities play a pivotal role in life science research, supporting a wide range of studies, from basic biology to clinical diagnostics. Despite their critical role, these facilities face persistent challenges, including reliance on manual operation, fragmented software ecosystems (metadata and file formats) and inconsistencies across hardware platforms. These issues undermine reproducibility and slow progress in generating robust scientific insights.

To address these challenges, the project aims to implement a smart microscopy solution — data-driven microscopy (DDM) — at the Lund University Bioimaging Centre (LBIC) and the Core Facility for Integrated Microscopy (CFIM) at the University of Copenhagen. Developed by the Nordenfelt group at Lund University (André et al., 2023), DDM has resulted in the spin-off company Cytely AB, which is the project’s industry partner.