activity
20192022
most citedFidelity Imposed Network Edit (FINE) for Solving Ill-Posed Image Reconstruction

10 citations · 29 across the 7 of their papers we have counts for

collaborators

9 papers

eess.IV20221 cited

LARO: Learned Acquisition and Reconstruction Optimization to accelerate Quantitative Susceptibility Mapping

Jinwei Zhang, Pascal Spincemaille, Hang Zhang +6

Quantitative susceptibility mapping (QSM) involves acquisition and reconstruction of a series of images at multi-echo time points to estimate tissue field, which prolongs scan time…

physics.med-ph2021

Motion Artifact Reduction in Quantitative Susceptibility Mapping using Deep Neural Network

Chao Li, Hang Zhang, Jinwei Zhang +3

An approach to reduce motion artifacts in Quantitative Susceptibility Mapping using deep learning is proposed. We use an affine motion model with randomly created motion profiles t…

eess.SP20211 cited

Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction

Jinwei Zhang, Hang Zhang, Chao Li +4

Quantitative imaging in MRI usually involves acquisition and reconstruction of a series of images at multi-echo time points, which possibly requires more scan time and specific rec…

eess.IV20216 cited

NeRD: Neural Representation of Distribution for Medical Image Segmentation

Hang Zhang, Rongguang Wang, Jinwei Zhang +5

We introduce Neural Representation of Distribution (NeRD) technique, a module for convolutional neural networks (CNNs) that can estimate the feature distribution by optimizing an u…

eess.IV2020

Probabilistic Dipole Inversion for Adaptive Quantitative Susceptibility Mapping

Jinwei Zhang, Hang Zhang, Mert Sabuncu +3

A learning-based posterior distribution estimation method, Probabilistic Dipole Inversion (PDI), is proposed to solve the quantitative susceptibility mapping (QSM) inverse problem…

eess.IV20208 cited

Extending LOUPE for K-space Under-sampling Pattern Optimization in Multi-coil MRI

Jinwei Zhang, Hang Zhang, Alan Wang +5

The previously established LOUPE (Learning-based Optimization of the Under-sampling Pattern) framework for optimizing the k-space sampling pattern in MRI was extended in three fold…