Author

Gareth A. Harman

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#artificial intelligence Preprint Oct 2026

Brain2Vec: A Self-Supervised 3D Foundation Model for Structural Brain MRI

Deep learning models have become essential tools in medical imaging, yet training them end-to-end for diverse tasks remains challenging due to limited labeled data and computational constraints. To address this, we introduce Brain2Vec, a foundation model pre-trained on 74,425 T1-weighted Magnetic Resonance Imaging (MRI...

Spiros Maggioros, G. Erus, Gareth A. Harman et al. · 0 citations

Preprint Aug 2026

GenFAR: A generalized representation of brain structure, derived from 49,246 multi-cohort MRIs via deep learning

GenFAR, a modular deep learning framework that learns general, clinically informed features from brain MRIs, is introduced, showing that using the learned feature representation can substantially increase the sample efficiency of secondary deep learning training tasks and models, as well as improve their accuracy.

V. Bashyam, G. Erus, Jun-Hao Wen et al. · 0 citations