A new expert-annotated dataset of embryo images with natural language morphological descriptions to support interpretable AI for transparent IVF embryo selection and patient communication.
Vision-language foundation models for medical imaging: a review of current practices and innovations
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VoxelFM learns robust 3D CT visual features via DINO self-distillation that transfer effectively to seven clinical task categories using frozen backbones and lightweight heads, outperforming prior CT foundation models even on report generation.
citing papers explorer
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Expert-Annotated Embryo Image Dataset with Natural Language Descriptions for Evidence-Based Patient Communication in IVF
A new expert-annotated dataset of embryo images with natural language morphological descriptions to support interpretable AI for transparent IVF embryo selection and patient communication.
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Learning Robust Visual Features in Computed Tomography Enables Efficient Transfer Learning for Clinical Tasks
VoxelFM learns robust 3D CT visual features via DINO self-distillation that transfer effectively to seven clinical task categories using frozen backbones and lightweight heads, outperforming prior CT foundation models even on report generation.