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20232025
most citedPhysics-Informed DeepMRI: Bridging the Gap from Heat Diffusion to k-Space Interpolation

3 citations · 6 across the 18 of their papers we have counts for

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cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

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…

cs.CV2023★ 3 cited

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…