5 citations · 16 across the 9 of their papers we have counts for
6 papers · 1 filter
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…
A New Deep Learning Method for Image Deblurring in Optical Microscopic Systems
Huangxuan Zhao, Ziwen Ke, Ningbo Chen +8
Deconvolution is the most commonly used image processing method to remove the blur caused by the point-spread-function (PSF) in optical imaging systems. While this method has been…
LANTERN: learn analysis transform network for dynamic magnetic resonance imaging with small dataset
Shanshan Wang, Yanxia Chen, Taohui Xiao +3
This paper proposes to learn analysis transform network for dynamic magnetic resonance imaging (LANTERN) with small dataset. Integrating the strength of CS-MRI and deep learning, t…
DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution
Shanshan Wang, Huitao Cheng, Leslie Ying +5
This paper proposes a multi-channel image reconstruction method, named DeepcomplexMRI, to accelerate parallel MR imaging with residual complex convolutional neural network. Differe…
Deep MRI Reconstruction: Unrolled Optimization Algorithms Meet Neural Networks
Dong Liang, Jing Cheng, Ziwen Ke +1
Image reconstruction from undersampled k-space data has been playing an important role for fast MRI. Recently, deep learning has demonstrated tremendous success in various fields a…
CRDN: Cascaded Residual Dense Networks for Dynamic MR Imaging with Edge-enhanced Loss Constraint
Ziwen Ke, Shanshan Wang, Huitao Cheng +4
Dynamic magnetic resonance (MR) imaging has generated great research interest, as it can provide both spatial and temporal information for clinical diagnosis. However, slow imaging…