VELVET-Med combines a sentence-aware TriBERT text encoder, hierarchical contrastive learning, and uni-modal self-supervision to pre-train 3D CT vision-language encoders on 38,875 scan-report pairs.
Medclip: Contrastive learning from unpaired medical images and text
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VELVET-Med: Vision and Efficient Language Pre-training for Volumetric Imaging Tasks in Medicine
VELVET-Med combines a sentence-aware TriBERT text encoder, hierarchical contrastive learning, and uni-modal self-supervision to pre-train 3D CT vision-language encoders on 38,875 scan-report pairs.