54 citations · 248 across the 37 of their papers we have counts for
9 papers · 1 filter
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…
DIRECT-Net: a unified mutual-domain material decomposition network for quantitative dual-energy CT imaging
Ting Su, Xindong Sun, Yikun Zhang +7
By acquiring two sets of tomographic measurements at distinct X-ray spectra, the dual-energy CT (DECT) enables quantitative material-specific imaging. However, the conventionally d…
DIR-DBTnet: Deep iterative reconstruction network for 3D digital breast tomosynthesis imaging
Ting Su, Xiaolei Deng, Zhenwei Wang +5
Purpose: The goal of this study is to develop a novel deep learning (DL) based reconstruction framework to improve the digital breast tomosynthesis (DBT) imaging performance. Metho…
Homotopic Gradients of Generative Density Priors for MR Image Reconstruction
Cong Quan, Jinjie Zhou, Yuanzheng Zhu +4
Deep learning, particularly the generative model, has demonstrated tremendous potential to significantly speed up image reconstruction with reduced measurements recently. Rather th…
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…
Estimation of angular sensitivity for X-ray interferometers with multiple phase gratings
Jianwei Chen, Jiecheng Yang, Peiping Zhu +5
Recently, X-ray interferometers with more than one phase grating have been developed for differential phase contrast (DPC) imaging. In this study, a novel framework is developed to…