XNAT Scout: Enabling Translational AI
January 22, 2026 | 11:00 AM – 12:00 PM
Virtual
Attend this webinar to learn more about XNAT Scout—a new extension of the XNAT imaging informatics platform that’s designed to close the gap between artificial intelligence (AI) model development and clinical deployment. Washington University’s Dr. Daniel Marcus will introduce XNAT Scout’s:
- architecture.
- key capabilities.
- early deployment experiences.
XNAT Scout provides structured tools for assembling training cohorts, managing annotations, benchmarking models, and monitoring performance over time. Integrated with XNAT’s mature imaging workflows and governance frameworks, it enables reproducible validation, multi-site collaboration, and deployment pathways aligned with clinical interoperability and security requirements. By unifying data curation, evaluation, and operationalization in one platform, XNAT Scout accelerates translation and supports health systems in safely adopting AI at scale.
About the Speaker
Daniel Marcus, Ph.D.
Dr. Marcus is a professor of radiology at Washington University School of Medicine. He’s also the director of the Computational Imaging Research Center—an interdisciplinary team of engineers, scientists, software developers, and informaticists who have the collective goal of enabling imaging in biomedical research. Dr. Marcus is a nationally recognized leader in medical imaging informatics and AI, whose work has significantly advanced translational research infrastructure and institutional capability. He is the architect and principal investigator of XNAT—a globally used, open-source imaging informatics platform funded by the Informatics Technology for Cancer Research (ITCR) program.