7 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…
CATNUS: Coordinate-Aware Thalamic Nuclei Segmentation Using T1-Weighted MRI
Anqi Feng, Zhangxing Bian, Samuel W. Remedios +6
Accurate segmentation of thalamic nuclei from magnetic resonance images is important due to the distinct roles of these nuclei in overall brain function and to their differential i…
Unsupervised learning of spatially varying regularization for diffeomorphic image registration
Junyu Chen, Shuwen Wei, Yihao Liu +5
Spatially varying regularization accommodates the deformation variations that may be necessary for different anatomical regions during deformable image registration. Historically,…
Segmenting Thalamic Nuclei: T1 Maps Provide a Reliable and Efficient Solution
Anqi Feng, Zhangxing Bian, Samuel W. Remedios +5
Accurate thalamic nuclei segmentation is crucial for understanding neurological diseases, brain functions, and guiding clinical interventions. However, the optimal inputs for segme…
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…