1 citations · 1 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
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…
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…