most citedADFA: Attention-augmented Differentiable top-k Feature Adaptation for Unsupervised Medical Anomaly Detection

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cs.CV2026

Towards Reliable Fetal Ultrasound Interpretation with Multi-Agent Collaboration

Xiaotian Hu, Mingxuan Liu, Junwei Huang +13

Automated fetal ultrasound interpretation requires a workflow from visual perception, including plane recognition and anatomical segmentation, to clinical understanding, including…

cs.CV2026

FetalAgents: A Multi-Agent System for Fetal Ultrasound Image and Video Analysis

Xiaotian Hu, Junwei Huang, Mingxuan Liu +9

Fetal ultrasound (US) is the primary imaging modality for prenatal screening, yet its interpretation relies heavily on the expertise of the clinician. Despite advances in deep lear…

cs.CV2023★ 1 cited

ADFA: Attention-augmented Differentiable top-k Feature Adaptation for Unsupervised Medical Anomaly Detection

Yiming Huang, Guole Liu, Yaoru Luo +1

The scarcity of annotated data, particularly for rare diseases, limits the variability of training data and the range of detectable lesions, presenting a significant challenge for…