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05/07/2022
Unsupervised Deep Unrolled Reconstruction Using Regularization by Denoising
Deep learning methods have been successfully used in various computer vi...
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06/22/2020
Deep Low-rank Prior in Dynamic MR Imaging
The deep learning methods have achieved attractive results in dynamic MR...
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02/27/2020
Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case
This paper establishes a kernel-based framework for reconstructing data ...
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02/03/2020
Deep Learning for Highly Accelerated Diffusion Tensor Imaging
Diffusion tensor imaging (DTI) is widely used to examine the human brain...
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12/20/2019
An Unsupervised Deep Learning Method for Parallel Cardiac MRI via Time-Interleaved Sampling
Deep learning has achieved good success in cardiac magnetic resonance im...
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08/07/2019
Model Learning: Primal Dual Networks for Fast MR imaging
Magnetic resonance imaging (MRI) is known to be a slow imaging modality ...
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07/26/2019
Deep MRI Reconstruction: Unrolled Optimization Algorithms Meet Neural Networks
Image reconstruction from undersampled k-space data has been playing an ...
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06/19/2019
Model-based Deep MR Imaging: the roadmap of generalizing compressed sensing model using deep learning
Accelerating magnetic resonance imaging (MRI) has been an ongoing resear...
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06/11/2019
DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution
This paper proposes a multi-channel image reconstruction method, named D...
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01/18/2019
CRDN: Cascaded Residual Dense Networks for Dynamic MR Imaging with Edge-enhanced Loss Constraint
Dynamic magnetic resonance (MR) imaging has generated great research int...
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12/27/2018