works on

From the 1 of 7 linked papers with an AI index.

most citedArtificial Intelligence for Detecting Fetal Orofacial Clefts and Advancing Medical Education

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2026

AnomExpert: Identifying and Selecting Anatomical Planes for Prenatal Ultrasound Anomaly Diagnosis

Jian Wang, Yang Yang, Ziheng Pan +4

The paper introduces AnomExpert, a framework that learns to identify anatomical planes and select disease-relevant planes in prenatal ultrasound images using only case-level labels…

cs.CV2026

FrameONE: Hierarchical Motion Modeling for Universal Multi-View Echocardiographic Keyframe Detection

Rusi Chen, Yuhao Huang, Hongyuan Zhang +4

Accurate detection of end-systole (ES) and end-diastole (ED) frames is fundamental to echocardiographic assessment. Existing methods are typically developed in a view-specific mann…

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…

eess.IV2025

MTCNet: Motion and Topology Consistency Guided Learning for Mitral Valve Segmentationin 4D Ultrasound

Rusi Chen, Yuanting Yang, Jiezhi Yao +12

Mitral regurgitation is one of the most prevalent cardiac disorders. Four-dimensional (4D) ultrasound has emerged as the primary imaging modality for assessing dynamic valvular mor…

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…