Foundation Models

Foundation models are increasingly discussed in imaging AI because they may change how systems are pretrained, adapted, and deployed across tasks and modalities. Their promise is broad, but clinical usefulness still depends on validation, integration, and operational fit.

This page tracks what foundation models mean in imaging without treating technical scale as proof of clinical value.

What This Page Covers

• Representation learning in imaging
• Transfer and adaptation across tasks
• Clinical relevance and deployment questions