collaborators

5 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

eess.IV2025

MoNetV2: Enhanced Motion Network for Freehand 3D Ultrasound Reconstruction

Mingyuan Luo, Xin Yang, Zhongnuo Yan +8

Three-dimensional (3D) ultrasound (US) aims to provide sonographers with the spatial relationships of anatomical structures, playing a crucial role in clinical diagnosis. Recently,…

eess.IV2025

FetalFlex: Anatomy-Guided Diffusion Model for Flexible Control on Fetal Ultrasound Image Synthesis

Yaofei Duan, Tao Tan, Zhiyuan Zhu +14

Fetal ultrasound (US) examinations require the acquisition of multiple planes, each providing unique diagnostic information to evaluate fetal development and screening for congenit…