3 papers
cs.CV2025
JotlasNet: Joint Tensor Low-Rank and Attention-based Sparse Unrolling Network for Accelerating Dynamic MRI
Yinghao Zhang, Haiyan Gui, Ningdi Yang +1
Joint low-rank and sparse unrolling networks have shown superior performance in dynamic MRI reconstruction. However, existing works mainly utilized matrix low-rank priors, neglecti…
eess.IV2025
T2LR-Net: An unrolling network learning transformed tensor low-rank prior for dynamic MR image reconstruction
Yinghao Zhang, Peng Li, Yue Hu
The tensor low-rank prior has attracted considerable attention in dynamic MR reconstruction. Tensor low-rank methods preserve the inherent high-dimensional structure of data, allow…
math.NA2024
Differentiable SVD based on Moore-Penrose Pseudoinverse for Inverse Imaging Problems
Yinghao Zhang, Yue Hu
Low-rank regularization-based deep unrolling networks have achieved remarkable success in various inverse imaging problems (IIPs). However, the singular value decomposition (SVD) i…