9 citations · 12 across the 4 of their papers we have counts for
8 papers
An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset
Wanyu Bian, Yunmei Chen, Xiaojing Ye +1
Purpose: This work aims at developing a generalizable MRI reconstruction model in the meta-learning framework. The standard benchmarks in meta-learning are challenged by learning o…
Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstruction
Qingchao Zhang, Mehrdad Alvandipour, Wenjun Xia +3
We propose a provably convergent method, called Efficient Learned Descent Algorithm (ELDA), for low-dose CT (LDCT) reconstruction. ELDA is a highly interpretable neural network arc…
Deep Parallel MRI Reconstruction Network Without Coil Sensitivities
Wanyu Bian, Yunmei Chen, Xiaojing Ye
We propose a novel deep neural network architecture by mapping the robust proximal gradient scheme for fast image reconstruction in parallel MRI (pMRI) with regularization function…
A Novel Learnable Gradient Descent Type Algorithm for Non-convex Non-smooth Inverse Problems
Qingchao Zhang, Xiaojing Ye, Hongcheng Liu +1
Optimization algorithms for solving nonconvex inverse problem have attracted significant interests recently. However, existing methods require the nonconvex regularization to be sm…
Extra Proximal-Gradient Inspired Non-local Network
Qingchao Zhang, Yunmei Chen
Variational method and deep learning method are two mainstream powerful approaches to solve inverse problems in computer vision. To take advantages of advanced optimization algorit…
Inverse Projection Representation and Category Contribution Rate for Robust Tumor Recognition
Xiao-Hui Yang, Li Tian, Yun-Mei Chen +3
Sparse representation based classification (SRC) methods have achieved remarkable results. SRC, however, still suffer from requiring enough training samples, insufficient use of te…