3 citations · 4 across the 2 of their papers we have counts for
5 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…
Deep Low-rank plus Sparse Network for Dynamic MR Imaging
Wenqi Huang, Ziwen Ke, Zhuo-Xu Cui +6
In dynamic magnetic resonance (MR) imaging, low-rank plus sparse (L+S) decomposition, or robust principal component analysis (PCA), has achieved stunning performance. However, the…
Is Each Layer Non-trivial in CNN?
Wei Wang, Yanjie Zhu, Zhuoxu Cui +1
Convolutional neural network (CNN) models have achieved great success in many fields. With the advent of ResNet, networks used in practice are getting deeper and wider. However, is…
A Nonconvex Nonsmooth Regularization Method for Compressed Sensing and Low-Rank Matrix Completion
Zhuo-Xu Cui, Qibin Fan
In this paper, nonconvex and nonsmooth models for compressed sensing (CS) and low rank matrix completion (MC) is studied. The problem is formulated as a nonconvex regularized leat…