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Image construction methods for phased array magnetic resonance imaging

Journal of magnetic resonance imaging, 2004-08, Vol.20 (2), p.306-314

2004

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Compressive sensing MR imaging based on adaptive tight frame and reference image

IET image processing, 2020-12, Vol.14 (14), p.3508-3515

2020

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Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction

IEEE transactions on medical imaging, 2021-09, Vol.40 (9), p.2306-2317

2021

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Learning Joint-Sparse Codes for Calibration-Free Parallel MR Imaging

IEEE transactions on medical imaging, 2018-01, Vol.37 (1), p.251-261

2018

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ReconResNet: Regularised residual learning for MR image reconstruction of Undersampled Cartesian and Radial data

Computers in biology and medicine, 2022-04, Vol.143, p.105321-105321, Article 105321

2022

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Specificity-Preserving Federated Learning for MR Image Reconstruction

IEEE transactions on medical imaging, 2023-07, Vol.42 (7), p.2010-2021

2023

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Suppressing motion artefacts in MRI using an Inception‐ResNet network with motion simulation augmentation

NMR in biomedicine, 2022-04, Vol.35 (4), p.e4225-n/a

2022

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A k‐space‐to‐image reconstruction network for MRI using recurrent neural network

Medical physics (Lancaster), 2021-01, Vol.48 (1), p.193-203

2021

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Efficient MR image reconstruction for compressed MR imaging

Medical image analysis, 2011-10, Vol.15 (5), p.670-679

2011

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Automated filter selection for suppression of Gibbs ringing artefacts in MRI

Magnetic resonance imaging, 2022-11, Vol.93, p.3-10

2022

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Compressed sensing MRI based on the hybrid regularization by denoising and the epigraph projection

Signal processing, 2020-05, Vol.170, p.107444, Article 107444

2020

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Domain knowledge augmentation of parallel MR image reconstruction using deep learning

Computerized medical imaging and graphics, 2021-09, Vol.92, p.101968-101968, Article 101968

2021

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Deep unfolding architecture for MRI reconstruction enhanced by adaptive noise maps

Biomedical signal processing and control, 2022-09, Vol.78, p.104016, Article 104016

2022

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Unsupervised learning of a deep neural network for metal artifact correction using dual‐polarity readout gradients

Magnetic resonance in medicine, 2020-01, Vol.83 (1), p.124-138

2020

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Learning a preconditioner to accelerate compressed sensing reconstructions in MRI

Magnetic resonance in medicine, 2022-04, Vol.87 (4), p.2063-2073

2022

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An MTL1TV non-convex regularization model for MR Image reconstruction using the alternating direction method of multipliers

Electronic research archive, 2024-05, Vol.32 (5), p.3433-3456

2024

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Compressed sensing MRI based on image decomposition model and group sparsity

Magnetic resonance imaging, 2019-07, Vol.60, p.101-109

2019

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Decentralised Agent-Based Medical Image Reconstruction

Procedia computer science, 2022, Vol.207, p.2106-2115

2022

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CNS wide simulation of flow resistance and drug transport due to spinal microanatomy

Journal of biomechanics, 2015-07, Vol.48 (10), p.2144-2154

2015

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A novel low-rank model for MRI using the redundant wavelet tight frame

Neurocomputing (Amsterdam), 2018-05, Vol.289, p.180-187

2018

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Prior information constrained alternating direction method of multipliers for longitudinal compressive sensing MR imaging

Neurocomputing (Amsterdam), 2020-02, Vol.376, p.128-140

2020

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Double total variation (DTV) regularization and Improved adaptive moment estimation (IADAM) optimization method for fast MR image reconstruction

Computer methods and programs in biomedicine, 2023-05, Vol.233, p.107463-107463, Article 107463

2023

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Composite splitting algorithms for convex optimization

Computer vision and image understanding, 2011-12, Vol.115 (12), p.1610-1622

2011

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Fast Parallel MR Image Reconstruction via B1-Based, Adaptive Restart, Iterative Soft Thresholding Algorithms (BARISTA)

IEEE transactions on medical imaging, 2015-02, Vol.34 (2), p.578-588

2015

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Reconstruction of compressively sampled MR images based on a local shrinkage thresholding algorithm with curvelet transform

Medical & biological engineering & computing, 2019-10, Vol.57 (10), p.2145-2158

2019

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Image construction methods for phased array magnetic resonance imaging

Compressive sensing MR imaging based on adaptive tight frame and reference image

Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction

Learning Joint-Sparse Codes for Calibration-Free Parallel MR Imaging

ReconResNet: Regularised residual learning for MR image reconstruction of Undersampled Cartesian and Radial data

Specificity-Preserving Federated Learning for MR Image Reconstruction

Suppressing motion artefacts in MRI using an Inception‐ResNet network with motion simulation augmentation

A k‐space‐to‐image reconstruction network for MRI using recurrent neural network

Efficient MR image reconstruction for compressed MR imaging

Automated filter selection for suppression of Gibbs ringing artefacts in MRI

Compressed sensing MRI based on the hybrid regularization by denoising and the epigraph projection

Domain knowledge augmentation of parallel MR image reconstruction using deep learning

Deep unfolding architecture for MRI reconstruction enhanced by adaptive noise maps

Unsupervised learning of a deep neural network for metal artifact correction using dual‐polarity readout gradients

Learning a preconditioner to accelerate compressed sensing reconstructions in MRI

An MTL1TV non-convex regularization model for MR Image reconstruction using the alternating direction method of multipliers

Compressed sensing MRI based on image decomposition model and group sparsity

Decentralised Agent-Based Medical Image Reconstruction

CNS wide simulation of flow resistance and drug transport due to spinal microanatomy

A novel low-rank model for MRI using the redundant wavelet tight frame

Prior information constrained alternating direction method of multipliers for longitudinal compressive sensing MR imaging

Double total variation (DTV) regularization and Improved adaptive moment estimation (IADAM) optimization method for fast MR image reconstruction

Composite splitting algorithms for convex optimization

Fast Parallel MR Image Reconstruction via B1-Based, Adaptive Restart, Iterative Soft Thresholding Algorithms (BARISTA)

Reconstruction of compressively sampled MR images based on a local shrinkage thresholding algorithm with curvelet transform

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