3 citations · 6 across the 18 of their papers we have counts for
18 papers
Flow-Guided Implicit Neural Representation for Motion-Aware Dynamic MRI Reconstruction
Baoqing Li, Yuanyuan Liu, Congcong Liu +6
Dynamic magnetic resonance imaging (dMRI) captures temporally-resolved anatomy but is often challenged by limited sampling and motion-induced artifacts. Conventional motion-compens…
Self-supervised Deep Unrolled Model with Implicit Neural Representation Regularization for Accelerating MRI Reconstruction
Jingran Xu, Yuanyuan Liu, Yuanbiao Yang +7
Magnetic resonance imaging (MRI) is a vital clinical diagnostic tool, yet its application is limited by prolonged scan times. Accelerating MRI reconstruction addresses this issue b…
HAVIR: HierArchical Vision to Image Reconstruction using CLIP-Guided Versatile Diffusion
Shiyi Zhang, Dong Liang, Hairong Zheng +1
The reconstruction of visual information from brain activity fosters interdisciplinary integration between neuroscience and computer vision. However, existing methods still face ch…
NeuroSwift: A Lightweight Cross-Subject Framework for fMRI Visual Reconstruction of Complex Scenes
Shiyi Zhang, Dong Liang, Yihang Zhou
Reconstructing visual information from brain activity via computer vision technology provides an intuitive understanding of visual neural mechanisms. Despite progress in decoding f…
HAVIR: HierArchical Vision to Image Reconstruction using CLIP-Guided Versatile Diffusion
Shiyi Zhang, Dong Liang, Hairong Zheng +1
Reconstructing visual information from brain activity bridges the gap between neuroscience and computer vision. Even though progress has been made in decoding images from fMRI usin…
Accurate myocardial T1 mapping at 5T using an improved MOLLI method: A validation study
Linqi Ge, Yinuo Zhao, Yubo Guo +7
Background: Accurate myocardial T1 mapping at 5T remains a technical challenge due to field inhomogeneity and prolonged T1 values. The aim of this study is to develop an accurate a…
K-space Diffusion Model Based MR Reconstruction Method for Simultaneous Multislice Imaging
Ting Zhao, Zhuoxu Cui, Congcong Liu +4
Simultaneous Multi-Slice(SMS) is a magnetic resonance imaging (MRI) technique which excites several slices concurrently using multiband radiofrequency pulses to reduce scanning tim…
Myocardial T1 mapping at 5T using multi-inversion recovery real-time spoiled GRE
Linqi Ge, Yihang Zhang, Huibin Zhu +6
Objective: To develop an accurate myocardial T1 mapping technique at 5T using Look-Locker-based multiple inversion-recovery with the real-time spoiled gradient echo (GRE) acquisiti…
Quantum Neural Network for Accelerated Magnetic Resonance Imaging
Shuo Zhou, Yihang Zhou, Congcong Liu +4
Magnetic resonance image reconstruction starting from undersampled k-space data requires the recovery of many potential nonlinear features, which is very difficult for algorithms t…
Optimized Magnetic Resonance Fingerprinting Using Ziv-Zakai Bound
Chaoguang Gong, Yue Hu, Peng Li +6
Magnetic Resonance Fingerprinting (MRF) has emerged as a promising quantitative imaging technique within the field of Magnetic Resonance Imaging (MRI), offers comprehensive insight…
Pediatric TSC-Related Epilepsy Classification from Clinical MR Images Using Quantum Neural Network
Ling Lin, Yihang Zhou, Zhanqi Hu +8
Tuberous sclerosis complex (TSC) manifests as a multisystem disorder with significant neurological implications. This study addresses the critical need for robust classification mo…
MR Optimized Reconstruction of Simultaneous Multi-Slice Imaging Using Diffusion Model
Ting Zhao, Zhuoxu Cui, Sen Jia +6
Diffusion model has been successfully applied to MRI reconstruction, including single and multi-coil acquisition of MRI data. Simultaneous multi-slice imaging (SMS), as a method fo…
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…
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…
Score-based Diffusion Models With Self-supervised Learning For Accelerated 3D Multi-contrast Cardiac Magnetic Resonance Imaging
Yuanyuan Liu, Zhuo-Xu Cui, Shucong Qin +6
Long scan time significantly hinders the widespread applications of three-dimensional multi-contrast cardiac magnetic resonance (3D-MC-CMR) imaging. This study aims to accelerate 3…
Physics-Informed DeepMRI: Bridging the Gap from Heat Diffusion to k-Space Interpolation
Zhuo-Xu Cui, Congcong Liu, Xiaohong Fan +11
In the field of parallel imaging (PI), alongside image-domain regularization methods, substantial research has been dedicated to exploring -space interpolation. However, the int…
Dynamic Dual-Graph Fusion Convolutional Network For Alzheimer's Disease Diagnosis
Fanshi Li, Zhihui Wang, Yifan Guo +6
In this paper, a dynamic dual-graph fusion convolutional network is proposed to improve Alzheimer's disease (AD) diagnosis performance. The following are the paper's main contribut…
Synthesizing PET images from High-field and Ultra-high-field MR images Using Joint Diffusion Attention Model
Taofeng Xie, Chentao Cao, Zhuoxu Cui +14
MRI and PET are crucial diagnostic tools for brain diseases, as they provide complementary information on brain structure and function. However, PET scanning is costly and involves…