3 citations · 3 across the 10 of their papers we have counts for
10 papers
Diffusion-Encoding Gaussian Field for Joint k-q dMRI Reconstruction
Zhibo Chen, Yajuan Huang, Yu Guan +3
Diffusion MRI requires repeated k-space acquisitions over multiple diffusion-encoding directions, making acquisition time dependent on both spatial and angular sampling. Existing j…
K-space Gaussian Representation for Parallel MRI
Yu Guan, Mingyu Hu, Jiale Hu +3
Accelerated magnetic resonance imaging (MRI) aims to recover the k-space signal from acquired measurements, where accurate estimation of missing samples is essential for high-fidel…
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…
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…
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…
Adaptive Mask-guided K-space Diffusion for Accelerated MRI Reconstruction
Qinrong Cai, Yu Guan, Zhibo Chen +3
As the deep learning revolution marches on, masked modeling has emerged as a distinctive approach that involves predicting parts of the original data that are proportionally masked…
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…
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…
DP-MDM: Detail-Preserving MR Reconstruction via Multiple Diffusion Models
Mengxiao Geng, Jiahao Zhu, Xiaolin Zhu +3
Detail features of magnetic resonance images play a cru-cial role in accurate medical diagnosis and treatment, as they capture subtle changes that pose challenges for doc-tors when…
Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI Reconstruction
Yu Guan, Chuanming Yu, Shiyu Lu +3
Most existing MRI reconstruction methods perform tar-geted reconstruction of the entire MR image without tak-ing specific tissue regions into consideration. This may fail to emphas…