activity
20232026
most citedExplainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Recurrent Contrastive Learning for Imbalanced Medical Image Classification

Zhiyuan Zhu, Xinling Meng, Junxuan Yu +15

Medical image classification often suffers from class imbalance due to the inherent disparities in disease incidence. Existing approaches, such as class resampling and loss reweigh…

eess.IV2025

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…

eess.IV2025

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…

eess.IV20241 cited

Explainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation

Junxuan Yu, Rusi Chen, Yongsong Zhou +7

Echocardiography video is a primary modality for diagnosing heart diseases, but the limited data poses challenges for both clinical teaching and machine learning training. Recently…

eess.IV2023

FFPN: Fourier Feature Pyramid Network for Ultrasound Image Segmentation

Chaoyu Chen, Xin Yang, Rusi Chen +7

Ultrasound (US) image segmentation is an active research area that requires real-time and highly accurate analysis in many scenarios. The detect-to-segment (DTS) frameworks have be…