collaborators

5 papers

cs.CV2026

Learning Where and What to Lift for Bi-planar X-ray-to-CT Reconstruction

Yifei Wu, Yicheng Wu, Qiang Ma +5

X-ray imaging can be approximately modeled as the projection of an underlying volumetric attenuation field, with each measurement recording the accumulated attenuation along a corr…

eess.IV2026

Cardiac Mesh Flow: One-Step Generation of 3D+t Cardiac Four-Chamber Meshes via Flow Matching

Qiang Ma, Qingjie Meng, Mengyun Qiao +3

Spatio-temporal (3D+t) generative modelling of cardiac shape and motion is crucial for understanding heart structure and function at population scale. Existing generative models fo…

cs.CV2026

AdamFlow: Adam-based Wasserstein Gradient Flows for Surface Registration in Medical Imaging

Qiang Ma, Qingjie Meng, Xin Hu +2

Surface registration plays an important role for anatomical shape analysis in medical imaging. Existing surface registration methods often face a trade-off between efficiency and r…

eess.IV2026

Learning a dynamic four-chamber shape model of the human heart for 95,695 UK Biobank participants

Qiang Ma, Qingjie Meng, Yicheng Wu +6

The human heart is a sophisticated system composed of four cardiac chambers with distinct shapes, which function in a coordinated manner. Existing shape models of the heart mainly…

eess.IV2025

CardiacFlow: 3D+t Four-Chamber Cardiac Shape Completion and Generation via Flow Matching

Qiang Ma, Qingjie Meng, Mengyun Qiao +3

Learning 3D+t shape completion and generation from multi-view cardiac magnetic resonance (CMR) images requires a large amount of high-resolution 3D whole-heart segmentations (WHS)…