by
Gus Iversen, Editor in Chief | November 05, 2025
The Mallinckrodt Institute of Radiology at Washington University School of Medicine is launching a new center focused on the development of AI-powered medical imaging tools aimed at improving diagnosis and patient-specific treatment strategies.
The Center for Computational and AI-enabled Imaging Sciences brings together researchers from WashU Medicine and the university’s McKelvey School of Engineering to build technologies that integrate data from various imaging modalities — including MR, X-ray, and digital pathology — with de-identified patient records to identify early disease indicators and guide clinical decisions.
"Integrating AI into imaging will enhance how we diagnose disease, predict its progression and tailor treatments to the unique needs of each patient," said Dr. Pamela Woodard, head of the Mallinckrodt Institute and the Elizabeth E. Mallinckrodt Professor.
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Among the AI tools already emerging from the collaboration are an algorithm that predicts breast cancer risk from mammograms and another that maps the brain for surgical planning. The new center will act as a hub for similar technologies, supporting both research and clinician training in image-based AI applications.
The center joins a network of AI-focused initiatives at WashU, including the Center for Health AI (CHAI) and the AI for Health Institute, which work across departments and with the BJC Health System to apply artificial intelligence to patient care and system efficiency.
Mark Anastasio, Ph.D., a computational imaging expert who previously chaired the Department of Bioengineering at the University of Illinois Urbana-Champaign, will lead the center. He will also serve as vice chair for imaging sciences and AI research at Mallinckrodt, and hold joint roles with the Institute for Informatics, Data Science & Biostatistics and the Siteman Cancer Center.
“Institutions with leading academic medical centers that unite medical data, clinical expertise and advanced AI research will lead the next revolution in healthcare,” Anastasio said.
The center will centralize imaging data from multiple departments to support a range of research and clinical use cases, with the goal of developing AI tools that enable more precise, individualized patient care.
