10 papers
Solving a Nonlinear Blind Inverse Problem for Tagged MRI with Physics and Deep Generative Priors
Zhangxing Bian, Shuwen Wei, Samuel W. Remedios +4
Tagged MRI enables tracking internal tissue motion non-invasively. It encodes motion by modulating anatomy with periodic tags, which deform along with tissue. However, the entangle…
Likelihood-Separable Diffusion Inference for Multi-Image MRI Super-Resolution
Samuel W. Remedios, Zhangxing Bian, Shuwen Wei +3
Diffusion models are the current state-of-the-art for solving inverse problems in imaging. Their impressive generative capability allows them to approximate sampling from a prior d…
Surrogate Supervision for Robust and Generalizable Deformable Image Registration
Yihao Liu, Junyu Chen, Lianrui Zuo +7
Objective: Deep learning-based deformable image registration has achieved strong accuracy, but remains sensitive to variations in input image characteristics such as artifacts, fie…
Pretraining Deformable Image Registration Networks with Random Images
Junyu Chen, Shuwen Wei, Yihao Liu +2
Recent advances in deep learning-based medical image registration have shown that training deep neural networks~(DNNs) does not necessarily require medical images. Previous work sh…
Brightness-Invariant Tracking Estimation in Tagged MRI
Zhangxing Bian, Shuwen Wei, Xiao Liang +10
Magnetic resonance (MR) tagging is an imaging technique for noninvasively tracking tissue motion in vivo by creating a visible pattern of magnetization saturation (tags) that defor…
Correlation Ratio for Unsupervised Learning of Multi-modal Deformable Registration
Xiaojian Chen, Yihao Liu, Shuwen Wei +3
In recent years, unsupervised learning for deformable image registration has been a major research focus. This approach involves training a registration network using pairs of movi…