3 citations · 5 across the 4 of their papers we have counts for
6 papers
SRR-Net: A Super-Resolution-Involved Reconstruction Method for High Resolution MR Imaging
Wenqi Huang, Sen Jia, Ziwen Ke +4
Improving the image resolution and acquisition speed of magnetic resonance imaging (MRI) is a challenging problem. There are mainly two strategies dealing with the speed-resolution…
Deep Manifold Learning for Dynamic MR Imaging
Ziwen Ke, Zhuo-Xu Cui, Wenqi Huang +8
Purpose: To develop a deep learning method on a nonlinear manifold to explore the temporal redundancy of dynamic signals to reconstruct cardiac MRI data from highly undersampled me…
An Unsupervised Deep Learning Method for Multi-coil Cine MRI
Ziwen Ke, Jing Cheng, Leslie Ying +3
Deep learning has achieved good success in cardiac magnetic resonance imaging (MRI) reconstruction, in which convolutional neural networks (CNNs) learn a mapping from the undersamp…
Accelerating MR Imaging via Deep Chambolle-Pock Network
Haifeng Wang, Jing Cheng, Sen Jia +8
Compressed sensing (CS) has been introduced to accelerate data acquisition in MR Imaging. However, CS-MRI methods suffer from detail loss with large acceleration and complicated pa…
T1rho Fractional-order Relaxation of Human Articular Cartilage
Lixian Zou, Haifeng Wang, Yanjie Zhu +8
T1rho imaging is a promising non-invasive diagnostic tool for early detection of articular cartilage degeneration. A mono-exponential model is normally used to describe the T1rho r…
DIMENSION: Dynamic MR Imaging with Both K-space and Spatial Prior Knowledge Obtained via Multi-Supervised Network Training
Shanshan Wang, Ziwen Ke, Huitao Cheng +4
Dynamic MR image reconstruction from incomplete k-space data has generated great research interest due to its capability in reducing scan time. Nevertheless, the reconstruction pro…