Generative AI and foundation models in radiology: applications, opportunities, and potential challenges
RADIOLOGY
Abstract
Foundation models can streamline imaging workflows, improve diagnostic accuracy, enable personalized treatment, and, via integrated generative artificial intelligence, create synthetic images to augment scarce real-world data; however, successful adoption requires explainability, trust, and workflow integration.
Abstract sourceCite this work
Neda Tavakoli, Zahra Shakeri, Vrushab Gowda, Konrad Samsel, Arash Bedayat, Ahmadreza Ghasemiesfe, Ulas Bagci, Albert Hsiao, Tim Leiner, James Carr, Daniel Kim, Amir Ali Rahsepar (2025). Generative AI and foundation models in radiology: applications, opportunities, and potential challenges. RADIOLOGY https://doi.org/10.1148/radiol.242961
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