2 citations · 3 across the 4 of their papers we have counts for
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Prototype Memory-Guided Training-Free Anomaly Classification and Localization in Prenatal Ultrasound
Huanwen Liang, Yuhao Huang, Xiliang Zhu +6
Prenatal anomaly classification and localization is of critical importance for fetal health and pregnancy management. Although ultrasound (US) is the primary modality for prenatal…
Artificial Intelligence for Detecting Fetal Orofacial Clefts and Advancing Medical Education
Yuanji Zhang, Yuhao Huang, Haoran Dou +28
Orofacial clefts are among the most common congenital craniofacial abnormalities, yet accurate prenatal detection remains challenging due to the scarcity of experienced specialists…
Medical-Knowledge Driven Multiple Instance Learning for Classifying Severe Abdominal Anomalies on Prenatal Ultrasound
Huanwen Liang, Jingxian Xu, Yuanji Zhang +11
Fetal abdominal malformations are serious congenital anomalies that require accurate diagnosis to guide pregnancy management and reduce mortality. Although AI has demonstrated sign…