A large examination-level ultrasound dataset with long-form reports enables simple LVLM fine-tuning to outperform prior complex methods.
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Introduces Zoom-then-Diagnose paradigm and uncertainty-aware reward in GRPO for confidence-aware ultrasound VQA, reporting 39.3% improvement in lesion localization across liver, breast, and thyroid datasets.
FADA is a selectively distilled unified vision-language model for fetal ultrasound that performs interpretation, classification, detection, and segmentation in one pipeline, achieves strong metrics, and deploys offline on mobile devices.
citing papers explorer
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Towards Real-World Ultrasound Understanding: Large Vision-Language Models from Multi-Image Examinations with Long-Form Reports
A large examination-level ultrasound dataset with long-form reports enables simple LVLM fine-tuning to outperform prior complex methods.
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Look-Closer-Then-Diagnose: Confidence-Aware Ultrasound VQA via Active Zooming
Introduces Zoom-then-Diagnose paradigm and uncertainty-aware reward in GRPO for confidence-aware ultrasound VQA, reporting 39.3% improvement in lesion localization across liver, breast, and thyroid datasets.
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FADA: Accessible fetal ultrasound interpretation and annotation with a selectively distilled unified vision-language model
FADA is a selectively distilled unified vision-language model for fetal ultrasound that performs interpretation, classification, detection, and segmentation in one pipeline, achieves strong metrics, and deploys offline on mobile devices.