AI RESEARCH
VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment
arXiv CS.LG
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ArXi:2605.16775v1 Announce Type: cross Self-supervised learning (SSL) has advanced medical image analysis be enabling learning form large unlabelled data. However, in brain magnetic resonance imaging (MRI), most 3D models remain specialized for either segmentation of classification, limiting their ability to generalize across datasets, imaging protocols,, and downstream tasks. This lack of transferability constrains the clinical utility of 3D MRI models, despite the availability of unlabeled volumetric data.