activity
20192026
most citedPhase-change metasurfaces for reconfigurable image processing

13 citations · 23 across the 13 of their papers we have counts for

collaborators

21 papers

cs.CV2026

Back to Physics: Operator-Guided Generative Paths for SMS MRI Reconstruction

Zhibo Chen, Yu Guan, Yajuan Huang +5

Simultaneous multi-slice (SMS) imaging with in-plane undersampling enables highly accelerated MRI but yields a strongly coupled inverse problem with deterministic inter-slice inter…

cs.CV2025

K-Syn: K-space Data Synthesis in Ultra Low-data Regimes

Guan Yu, Zhang Jianhua, Liang Dong +1

Owing to the inherently dynamic and complex characteristics of cardiac magnetic resonance (CMR) imaging, high-quality and diverse k-space data are rarely available in practice, whi…

physics.med-ph2025

Diffusion-Assisted Frequency Attention Model for Whole-body Low-field MRI Reconstruction

Xin Xie, Yu Guan, Zhuoxu Cui +2

By integrating the generative strengths of diffusion models with the representation capabilities of frequency-domain attention, DFAM effectively enhances reconstruction performance…

physics.optics202413 cited

Phase-change metasurfaces for reconfigurable image processing

Tingting Liu, Jumin Qiu, Tianbao Yu +3

Optical metasurfaces have enabled high-speed, low-power image processing within a compact footprint. However, reconfigurable imaging in such flat devices remains a critical challen…

eess.IV2024

Sub-DM:Subspace Diffusion Model with Orthogonal Decomposition for MRI Reconstruction

Yu Guan, Qinrong Cai, Wei Li +3

Diffusion model-based approaches recently achieved re-markable success in MRI reconstruction, but integration into clinical routine remains challenging due to its time-consuming co…

eess.IV2024

Zero-shot Dynamic MRI Reconstruction with Global-to-local Diffusion Model

Yu Guan, Kunlong Zhang, Qi Qi +5

Diffusion models have recently demonstrated considerable advancement in the generation and reconstruction of magnetic resonance imaging (MRI) data. These models exhibit great poten…