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20242026
most citedExplainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation

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

collaborators

5 papers

cs.CV2026

Rethinking Medical Landmark Localization with Prototype Learning-based Progressive Offset Correction

Jingxian Xu, Yuhao Huang, Rusi Chen +2

Accurate landmark localization in medical images is a fundamental step for quantitative clinical measurement and downstream analysis. Existing localization methods have advanced, a…

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…

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…

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…

cs.CV2024

Fine-grained Context and Multi-modal Alignment for Freehand 3D Ultrasound Reconstruction

Zhongnuo Yan, Xin Yang, Mingyuan Luo +4

Fine-grained spatio-temporal learning is crucial for freehand 3D ultrasound reconstruction. Previous works mainly resorted to the coarse-grained spatial features and the separated…