5 papers · 1 filter
Learning to Beat: Phenotype-Guided Latent Flow with Regional Motion Priors for Biventricular Motion Synthesis
Xuan Yang, Xiaohan Yuan, Hao Li +4
Full-cycle biventricular geometry is essential for characterizing cardiac function. However, dense and temporally consistent 3D+t biventricular meshes are not routinely available,…
Echo4DIR: 4D Implicit Heart Reconstruction from 2D Echocardiography Videos
Yanan Liu, Qinya Li, Hao Zhang +5
Reconstructing 4D (3D+t) cardiac geometry from sparse 2D echocardiography is highly desirable yet fundamentally challenged by geometric ambiguity and temporal discontinuity. To tac…
RePCM: Region-Specific and Phenotype-Adaptive Bi-Ventricular Cardiac Motion Synthesis
Xuan Yang, Xiaohan Yuan, Hao Li +3
Cardiac motion over a cardiac cycle is crucial for quantifying regional function and is strongly affected by cardiovascular diseases. Since temporally dense mesh sequences are diff…
Astra: a generalizable report generation foundation model for 3D computed tomography
Zhuhao Wang, Fang Chen, Chaohui Yu +19
Interpreting computed tomography (CT) requires review of hundreds of volumetric slices and remains time-intensive and expertise-dependent. Automated CT report generation offers a p…
HGGT: Robust and Flexible 3D Hand Mesh Reconstruction from Uncalibrated Images
Yumeng Liu, Xiao-Xiao Long, Marc Habermann +5
Recovering high-fidelity 3D hand geometry from images is a critical task in computer vision, holding significant value for domains such as robotics, animation and VR/AR. Crucially,…