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20242026
most citedVector Field Attention for Deformable Image Registration

2 citations · 4 across the 12 of their papers we have counts for

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8 papers · 1 filter

eess.IV2026

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…

eess.IV2025

Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges

Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51

Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…

eess.IV2025

Deep learning-derived arterial input function for dynamic brain PET

Junyu Chen, Zirui Jiang, Jennifer M. Coughlin +4

Dynamic positron emission tomography (PET) imaging combined with radiotracer kinetic modeling is a powerful technique for visualizing biological processes in the brain, offering va…

eess.IV2025

Beyond the LUMIR challenge: The pathway to foundational registration models

Junyu Chen, Shuwen Wei, Joel Honkamaa +33

Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. Image registration, a foundati…

eess.IV2025

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…

eess.IV2024

Unsupervised Learning of Multi-modal Affine Registration for PET/CT

Junyu Chen, Yihao Liu, Shuwen Wei +2

Affine registration plays a crucial role in PET/CT imaging, where aligning PET with CT images is challenging due to their respective functional and anatomical representations. Desp…

eess.IV2024

From Registration Uncertainty to Segmentation Uncertainty

Junyu Chen, Yihao Liu, Shuwen Wei +3

Understanding the uncertainty inherent in deep learning-based image registration models has been an ongoing area of research. Existing methods have been developed to quantify both…

eess.IV2024★ 1 cited

Is Registering Raw Tagged-MR Enough for Strain Estimation in the Era of Deep Learning?

Zhangxing Bian, Ahmed Alshareef, Shuwen Wei +7

Magnetic Resonance Imaging with tagging (tMRI) has long been utilized for quantifying tissue motion and strain during deformation. However, a phenomenon known as tag fading, a grad…