2 citations · 2 across the 4 of their papers we have counts for
11 papers
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…
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…
ADAptation: Reconstruction-based Unsupervised Active Learning for Breast Ultrasound Diagnosis
Yaofei Duan, Yuhao Huang, Xin Yang +9
Deep learning-based diagnostic models often suffer performance drops due to distribution shifts between training (source) and test (target) domains. Collecting and labeling suffici…
Accurate and Efficient Fetal Birth Weight Estimation from 3D Ultrasound
Jian Wang, Qiongying Ni, Hongkui Yu +15
Accurate fetal birth weight (FBW) estimation is essential for optimizing delivery decisions and reducing perinatal mortality. However, clinical methods for FBW estimation are ineff…
MReg: A Novel Regression Model with MoE-based Video Feature Mining for Mitral Regurgitation Diagnosis
Zhe Liu, Yuhao Huang, Lian Liu +9
Color Doppler echocardiography is a crucial tool for diagnosing mitral regurgitation (MR). Recent studies have explored intelligent methods for MR diagnosis to minimize user depend…
UltraTwin: Towards Cardiac Anatomical Twin Generation from Multi-view 2D Ultrasound
Junxuan Yu, Yaofei Duan, Yuhao Huang +22
Echocardiography is routine for cardiac examination. However, 2D ultrasound (US) struggles with accurate metric calculation and direct observation of 3D cardiac structures. Moreove…