6 papers
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…
High-dimensional Embedding Prior for Noisy K-space Domain MRIReconstruction
Yu Guan, Tianjia Huang, Qinrong Cai +3
Magnetic resonance imaging (MRI) reconstruction under realistic acquisition conditions can be fundamentally viewed as estimating the underlying k-space distribution from incomplete…
A multi-modal vision-language model for generalizable annotation-free pathology localization
Hao Yang, Hong-Yu Zhou, Jiarun Liu +12
Existing deep learning models for defining pathology from clinical imaging data rely on expert annotations and lack generalization capabilities in open clinical environments. Here,…
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…
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…