Neuro-JEPA Foundation Model Pretrains on 1.5 Million Brain MRI Scans

Learning Sparse Latent Predictive Foundation Model for Multimodal Neuroimaging

This paper introduces Neuro-JEPA, a foundation model that combines a latent predictive objective with a Mixture-of-Experts architecture to encode brain MRI across core T1w, T2w, and fluid-suppressed FLAIR imaging (FLAIR).

Neuro-JEPA was pretrained on 1,551,862 scans from 428,647 studies after modality-specific preprocessing with data curation across three core structural brain MRI sequences.