13 citations · 28 across the 16 of their papers we have counts for
16 papers
Simultaneous q-Space Sampling Optimization and Reconstruction for Fast and High-fidelity Diffusion Magnetic Resonance Imaging
Jing Yang, Jian Cheng, Cheng Li +4
Diffusion Magnetic Resonance Imaging (dMRI) plays a crucial role in the noninvasive investigation of tissue microstructural properties and structural connectivity in the \textit{in…
Super resolution dual-layer CBCT imaging with model-guided deep learning
Jiongtao Zhu, Ting Su, Xin Zhang +6
Objective: This study aims at investigating a novel super resolution CBCT imaging technique with the dual-layer flat panel detector (DL-FPD). Approach: In DL-FPD based CBCT imaging…
Self-Supervised Federated Learning for Fast MR Imaging
Juan Zou, Cheng Li, Ruoyou Wu +3
Federated learning (FL) based magnetic resonance (MR) image reconstruction can facilitate learning valuable priors from multi-site institutions without violating patient's privacy…
Model-based Federated Learning for Accurate MR Image Reconstruction from Undersampled k-space Data
Ruoyou Wu, Cheng Li, Juan Zou +3
Deep learning-based methods have achieved encouraging performances in the field of magnetic resonance (MR) image reconstruction. Nevertheless, to properly learn a powerful and robu…
SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI
Zhuo-Xu Cui, Chentao Cao, Yue Wang +6
Diffusion models have emerged as a leading methodology for image generation and have proven successful in the realm of magnetic resonance imaging (MRI) reconstruction. However, exi…
SPIRiT-Diffusion: SPIRiT-driven Score-Based Generative Modeling for Vessel Wall imaging
Chentao Cao, Zhuo-Xu Cui, Jing Cheng +4
Diffusion model is the most advanced method in image generation and has been successfully applied to MRI reconstruction. However, the existing methods do not consider the character…