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20182026
most citedInformation-based Disentangled Representation Learning for Unsupervised MR Harmonization

6 citations · 18 across the 26 of their papers we have counts for

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13 papers · 1 filter

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

The Brain Resection Multimodal Image Registration (ReMIND2Reg) 2025 Challenge

Reuben Dorent, Laura Rigolo, Colin P. Galvin +8

Accurate intraoperative image guidance is critical for achieving maximal safe resection in brain tumor surgery, yet neuronavigation systems based on preoperative MRI lose accuracy…

cs.CV2025

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…

cs.CV2025

ECLARE: Efficient cross-planar learning for anisotropic resolution enhancement

Samuel W. Remedios, Shuwen Wei, Shuo Han +6

In clinical imaging, magnetic resonance (MR) image volumes are often acquired as stacks of 2D slices with decreased scan times, improved signal-to-noise ratio, and image contrasts…

cs.CV2024

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,…