activity
20232026
most citedJoint Diffusion: Mutual Consistency-Driven Diffusion Model for PET-MRI Co-Reconstruction

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Hypothesize, Evaluate, Refine: A Scientific Agent for PDE Discovery with Unknown Spatial Coefficient Fields

YuJie Huang, WenWu He, ZhuoEr Lin +3

Discovering PDEs in heterogeneous media requires jointly identifying the governing operator and the unknown spatial fields that parameterize it. These tasks are coupled: changing f…

cs.CV2025

Towards Globally Predictable k-Space Interpolation: A White-box Transformer Approach

Chen Luo, Qiyu Jin, Taofeng Xie +7

Interpolating missing data in k-space is essential for accelerating imaging. However, existing methods, including convolutional neural network-based deep learning, primarily exploi…

eess.IV2025

DUN-SRE: Deep Unrolling Network with Spatiotemporal Rotation Equivariance for Dynamic MRI Reconstruction

Yuliang Zhu, Jing Cheng, Qi Xie +7

Dynamic Magnetic Resonance Imaging (MRI) exhibits transformation symmetries, including spatial rotation symmetry within individual frames and temporal symmetry along the time dimen…

cs.CV2024

Joint PET-MRI Reconstruction with Diffusion Stochastic Differential Model

Taofeng Xie, Zhuoxu Cui, Congcong Liu +9

PET suffers from a low signal-to-noise ratio. Meanwhile, the k-space data acquisition process in MRI is time-consuming by PET-MRI systems. We aim to accelerate MRI and improve PET…

eess.IV2024

Diff-DTI: Fast Diffusion Tensor Imaging Using A Feature-Enhanced Joint Diffusion Model

Lang Zhang, Jinling He, Dong Liang +2

Magnetic resonance diffusion tensor imaging (DTI) is a critical tool for neural disease diagnosis. However, long scan time greatly hinders the widespread clinical use of DTI. To ac…

eess.IV2023★ 1 cited

Joint Diffusion: Mutual Consistency-Driven Diffusion Model for PET-MRI Co-Reconstruction

Taofeng Xie, Zhuo-Xu Cui, Chen Luo +10

Positron Emission Tomography and Magnetic Resonance Imaging (PET-MRI) systems can obtain functional and anatomical scans. PET suffers from a low signal-to-noise ratio. Meanwhile, t…

cs.CV2023

Convex Latent-Optimized Adversarial Regularizers for Imaging Inverse Problems

Huayu Wang, Chen Luo, Taofeng Xie +4

Recently, data-driven techniques have demonstrated remarkable effectiveness in addressing challenges related to MR imaging inverse problems. However, these methods still exhibit ce…