collaborators

5 papers

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…

cs.CV2026

Virtual Full-stack Scanning of Brain MRI via Imputing Any Quantised Code

Yicheng Wu, Tao Song, Zhonghua Wu +5

Magnetic resonance imaging (MRI) is a powerful and versatile imaging technique, offering a wide spectrum of information about the anatomy by employing different acquisition modalit…

cs.CV2026

Flow Matching-enabled Test-Time Refinement for Unsupervised Cardiac MR Registration

Yunguan Fu, Wenjia Bai, Wen Yan +3

Diffusion-based unsupervised image registration has been explored for cardiac cine MR, but expensive multi-step inference limits practical use. We propose FlowReg, a flow-matching…

cs.CV2026

SAM-aware Test-time Adaptation for Universal Medical Image Segmentation

Jianghao Wu, Yicheng Wu, Yutong Xie +7

Leveraging the Segment Anything Model (SAM) for medical image segmentation remains challenging due to its limited adaptability across diverse medical domains. Although fine-tuned v…

eess.IV2024

Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation

Kate Čevora, Ben Glocker, Wenjia Bai

Deep learning-based medical image segmentation has seen tremendous progress over the last decade, but there is still relatively little transfer into clinical practice. One of the m…