精选理由
密歇根大学NeuroVFM，用Vol-JEPA在524万MRI/CT上无监督训练，学脑解剖和病理，无需放射报告。
密歇根大学提出NeuroVFM，在524万临床MRI和CT体积上训练。其Vol-JEPA算法将I-JEPA和V-JEPA扩展到三维医学影像。该模型无需放射学报告标签即可学习脑部解剖和病理。
原文 · marktechpost
Meet NeuroVFM: A New Neuroimaging Foundation Model Trained With Vol-JEPA on Uncurated Clinical MRI and CT Volumes
NeuroVFM is a generalist neuroimaging foundation model from the University of Michigan, trained on 5.24M clinical MRI and CT volumes. Its Vol-JEPA base extends I-JEPA and V-JEPA to volumetric medical imaging, learning brain anatomy and pathology without radiology-report labels. The post Meet NeuroVFM: A New Neuroimaging Foundation Model Trained With Vol-JEPA on Uncurated Clinical MRI and CT Volumes appeared first on MarkTechPost .