13 citations · 54 across the 19 of their papers we have counts for
6 papers · 1 filter
DULDA: Dual-domain Unsupervised Learned Descent Algorithm for PET image reconstruction
Rui Hu, Yunmei Chen, Kyungsang Kim +3
Deep learning based PET image reconstruction methods have achieved promising results recently. However, most of these methods follow a supervised learning paradigm, which rely heav…
STPDnet: Spatial-temporal convolutional primal dual network for dynamic PET image reconstruction
Rui Hu, Jianan Cui, Chengjin Yu +2
Dynamic positron emission tomography (dPET) image reconstruction is extremely challenging due to the limited counts received in individual frame. In this paper, we propose a spatia…
A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesis
Wanyu Bian, Qingchao Zhang, Xiaojing Ye +1
Generating multi-contrasts/modal MRI of the same anatomy enriches diagnostic information but is limited in practice due to excessive data acquisition time. In this paper, we propos…
An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities
Wanyu Bian, Yunmei Chen, Xiaojing Ye
Goal: This work aims at developing a novel calibration-free fast parallel MRI (pMRI) reconstruction method incorporate with discrete-time optimal control framework. The reconstruct…
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…