SOURCE-LINKED INTELLIGENCE
A generalizable structural brain MRI foundation model built through dual-priority federated pretraining
Foundation models hold promise for generalizable analysis of structural brain magnetic resonance imaging (MRI) across development, aging and disease. However, existing models are typically built through centralized pretraining on pooled data, despite privacy and governance constraints. Such pooling optimization can overemphasize cohort size and overlook complementary information from smaller, specialized cohorts. Here we present BrainFedFM, a structural brain MRI foundation model federatively pretrained on 164,707 three-dimensional scans drawn from diverse real-world data distributions and org
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-23T09:29:01.000Z
First collected: 2026-09-24T01:22:21.678Z. This is not the publication date.