activity
20192022
most citedDeep Low-rank Prior in Dynamic MR Imaging

2 citations · 5 across the 7 of their papers we have counts for

collaborators

9 papers

eess.IV20202 cited

Deep Low-rank Prior in Dynamic MR Imaging

Ziwen Ke, Wenqi Huang, Jing Cheng +8

The deep learning methods have achieved attractive performance in dynamic MR cine imaging. However, all of these methods are only driven by the sparse prior of MR images, while the…

physics.med-ph2020

Positive Contrast Susceptibility MR Imaging Using GPU-based Primal-Dual Algorithm

Haifeng Wang, Fang Cai, Caiyun Shi +7

The susceptibility-based positive contrast MR technique was applied to estimate arbitrary magnetic susceptibility distributions of the metallic devices using a kernel deconvolution…

eess.IV2019

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…

eess.IV2019

Model Learning: Primal Dual Networks for Fast MR imaging

Jing Cheng, Haifeng Wang, Leslie Ying +1

Magnetic resonance imaging (MRI) is known to be a slow imaging modality and undersampling in k-space has been used to increase the imaging speed. However, image reconstruction from…

cs.CV2019

Model-based Deep Medical Imaging: the roadmap of generalizing iterative reconstruction model using deep learning

Jing Cheng, Haifeng Wang, Yanjie Zhu +10

Medical imaging is playing a more and more important role in clinics. However, there are several issues in different imaging modalities such as slow imaging speed in MRI, radiation…

eess.IV20191 cited

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…