2 citations · 4 across the 12 of their papers we have counts for
13 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…
Additive Manufacturing-Facilitated Blow Molding for Functional Thin-Walled Polymeric Structures
Junyu Chen, Dotan Ilssar, Dennis M. Kochmann
Thin-walled structures capable of large, reversible deformation are key to multistable structures, origami, kirigami, and soft robotics. However, conventional fabrication technique…
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…
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…
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…
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…
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…
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…
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,…
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…
Vector Field Attention for Deformable Image Registration
Yihao Liu, Junyu Chen, Lianrui Zuo +2
Deformable image registration establishes non-linear spatial correspondences between fixed and moving images. Deep learning-based deformable registration methods have been widely s…
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…
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…