Recent Advances in AI for Medical Imaging: Progress, Challenges, and Future Directions

Artificial intelligence has driven significant advances in medical imaging, improving tasks such as image reconstruction, diagnosis, and clinical decision support across modalities including MRI, CT, X-ray, and pathology. This tutorial provides an up-to-date overview of key paradigms in the field, including physics-informed learning, medical foundation models, and collaborative approaches such as federated and multi-agent systems. It examines major challenges such as generalization, interpretability, data heterogeneity, and privacy constraints, while highlighting emerging solutions and open research directions. The tutorial aims to offer a comprehensive perspective on the development and deployment of reliable, clinically relevant AI systems for medical imaging.