Generating Patient-like Phantoms Using Fully Unsupervised Deformable Image Registration with Convolutional Neural Networks. - Junyu Chen 002; Ye Li; Eric C. Frey (CoRR, 2019)

ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration. - Junyu Chen 002; Yufan He; Eric C. Frey; Ye Li; Yong Du 002 (CoRR, 2021)

Learning Fuzzy Clustering for SPECT/CT Segmentation via Convolutional Neural Networks. - Junyu Chen 002; Ye Li; Licia P. Luna; Hyun Woo Chung; Steven P. Rowe; Yong Du 002; Lilja B. Solnes; Eric C. Frey (CoRR, 2021)

A Noise-Level-Aware Framework for PET Image Denoising. - Ye Li; Jianan Cui; Junyu Chen 002; Guodong Zeng; Scott Wollenweber; Floris Jansen; Se-In Jang; Kyung Sang Kim; Kuang Gong; Quanzheng Li (MLMIR@MICCAI, 2022)

Unsupervised Learning of Diffeomorphic Image Registration via TransMorph. - Junyu Chen 002; Eric C. Frey; Yong Du 002 (WBIR, 2022)

Investigation of Network Architecture for Multimodal Head-and-Neck Tumor Segmentation. - Ye Li; Junyu Chen 002; Se-In Jang; Kuang Gong; Quanzheng Li (CoRR, 2022)

TransMorph: Transformer for unsupervised medical image registration. - Junyu Chen 002; Eric C. Frey; Yufan He; William Paul Segars; Ye Li; Yong Du 002 (Medical Image Anal., 2022)

MomentaMorph: Unsupervised Spatial-Temporal Registration with Momenta, Shooting, and Correction. - Zhangxing Bian; Shuwen Wei; Yihao Liu 003; Junyu Chen 002; Jiachen Zhuo; Fangxu Xing; Jonghye Woo; Aaron Carass; Jerry L. Prince (MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI, 2023)

Deformable Cross-Attention Transformer for Medical Image Registration. - Junyu Chen 002; Yihao Liu 003; Yufan He; Yong Du 002 (MLMI@MICCAI (1), 2023)

SwinCross: Cross-modal Swin Transformer for Head-and-Neck Tumor Segmentation in PET/CT Images. - Gary Y. Li; Junyu Chen 002; Se-In Jang; Kuang Gong; Quanzheng Li (CoRR, 2023)

Spatially-varying Regularization with Conditional Transformer for Unsupervised Image Registration. - Junyu Chen 002; Yihao Liu 003; Yufan He; Yong Du 002 (CoRR, 2023)

Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives. - Jun Li 103; Junyu Chen 002; Yucheng Tang; Ce Wang; Bennett A. Landman; S. Kevin Zhou (Medical Image Anal., 2023)

From Registration Uncertainty to Segmentation Uncertainty. - Junyu Chen 002; Yihao Liu 003; Shuwen Wei; Zhangxing Bian; Aaron Carass; Yong Du 002 (ISBI, 2024)

Is Registering Raw Tagged-MR Enough for Strain Estimation in the Era of Deep Learning? - Zhangxing Bian; Ahmed Alshareef; Shuwen Wei; Junyu Chen 002; Yuli Wang; Jonghye Woo; Dzung L. Pham; Jiachen Zhuo; Aaron Carass; Jerry L. Prince (CoRR, 2024)

Vector Field Attention for Deformable Image Registration. - Yihao Liu 003; Junyu Chen 002; Lianrui Zuo; Aaron Carass; Jerry L. Prince (CoRR, 2024)

Unsupervised learning of spatially varying regularization for diffeomorphic image registration. - Junyu Chen 002; Shuwen Wei; Yihao Liu 003; Zhangxing Bian; Yufan He; Aaron Carass; Harrison X. Bai; Yong Du 002 (CoRR, 2024)

Spach Transformer: Spatial and Channel-Wise Transformer Based on Local and Global Self-Attentions for PET Image Denoising. - Se-In Jang; Tinsu Pan; Ye Li; Pedram Heidari; Junyu Chen 002; Quanzheng Li; Kuang Gong (IEEE Trans. Medical Imaging, 2024)

On Finite Difference Jacobian Computation in Deformable Image Registration. - Yihao Liu 003; Junyu Chen 002; Shuwen Wei; Aaron Carass; Jerry L. Prince (Int. J. Comput. Vis., 2024)

A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond. - Junyu Chen 002; Yihao Liu 003; Shuwen Wei; Zhangxing Bian; Shalini Subramanian; Aaron Carass; Jerry L. Prince; Yong Du 002 (Medical Image Anal., 2025)

Beyond the LUMIR challenge: The pathway to foundational registration models. - Junyu Chen 002; Shuwen Wei; Joel Honkamaa; Pekka Marttinen; Hang Zhang; Min Liu; Yichao Zhou; Zuopeng Tan; Zhuoyuan Wang; Yi Wang; Hongchao Zhou; Shunbo Hu; et al. (CoRR, 2025)

Pretraining Deformable Image Registration Networks with Random Images. - Junyu Chen 002; Shuwen Wei; Yihao Liu 003; Aaron Carass; Yong Du 002 (CoRR, 2025)