FM2MRI

FM2MRI aims to build the first foundation model for MRI modality synthesis and segmentation, combining Mixture of Experts and Retrieval Augmented Generation to tackle scarce medical imaging settings — rare pathologies and costly protocols such as DCE-MRI perfusion maps — where only limited training data is available. The project investigates unified brain MRI encoders, prompt-guided multi-task learning for joint segmentation and synthesis, and privacy-preserving customization through external database retrieval, aiming for a flexible, generalizable and locally deployable foundation model for clinical use.