1 citations · 1 across the 4 of their papers we have counts for
4 papers
Revisiting Global Token Mixing in Task-Dependent MRI Restoration: Insights from Minimal Gated CNN Baselines
Xiangjian Hou, Chao Qin, Chang Ni +3
Global token mixing, implemented via self-attention or state-space sequence models, has become a popular model design choice for MRI restoration. However, MRI restoration tasks dif…
Unified and Semantically Grounded Domain Adaptation for Medical Image Segmentation
Xin Wang, Yin Guo, Jiamin Xia +5
Most prior unsupervised domain adaptation approaches for medical image segmentation are narrowly tailored to either the source-accessible setting, where adaptation is guided by sou…
RemInD: Remembering Anatomical Variations for Interpretable Domain Adaptive Medical Image Segmentation
Xin Wang, Yin Guo, Kaiyu Zhang +4
This work presents a novel Bayesian framework for unsupervised domain adaptation (UDA) in medical image segmentation. While prior works have explored this clinically significant ta…
Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image Registration
Xinzhe Luo, Xin Wang, Linda Shapiro +3
This article presents a general Bayesian learning framework for multi-modal groupwise image registration. The method builds on probabilistic modelling of the image generative proce…