Webinar: Making Bioimaging Data Discoverable, Accessible, and Understandable with AI

Learn how foundation models trained on CryoET datasets enhance image categorisation, and see how interactive AI assistants in the BioImage Archive streamline tasks like cell counting and segmentation without downloading massive files.

This talk explores two approaches to making bioimaging data discoverable, accessible, and understandable through AI and RI-SCALE’s Data Exploration Platforms. First, we discuss training a foundation model on a large cryo-electron tomography (cryo-ET) dataset to support image categorisation, interpretation, and quantitative analysis. We then explore how AI-powered assistants can help users navigate the BioImage Archive, find suitable tools, and perform tasks such as cell counting and segmentation, making data exploration and analysis accessible to researchers with varying levels of technical expertise.

Target Audience: Life scientists, bioimage analysts, CryoET specialists, and developers building large-scale bioimaging AI models.

This webinar is organized by RI-SCALE and is part of a series that showcases how the RI-SCALE Data Exploitation Platform (DEP) combines cutting-edge AI models, scalable computing, and FAIR data services to deliver real-world value across major European Research Infrastructures. Learn more about RI-SCALE and the ongoing Open Call, offering external communities direct support to onboard onto the platform, here.