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09/02/2023
Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI Reconstruction
Most existing MRI reconstruction methods perform tar-geted reconstructio...
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08/30/2023
Stage-by-stage Wavelet Optimization Refinement Diffusion Model for Sparse-View CT Reconstruction
Diffusion models have emerged as potential tools to tackle the challenge...
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08/30/2023
Physics-Informed DeepMRI: Bridging the Gap from Heat Diffusion to k-Space Interpolation
In the field of parallel imaging (PI), alongside image-domain regulariza...
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12/15/2022
Universal Generative Modeling in Dual-domain for Dynamic MR Imaging
Dynamic magnetic resonance image reconstruction from incomplete k-space ...
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12/11/2022
Low-rank Tensor Assisted K-space Generative Model for Parallel Imaging Reconstruction
Although recent deep learning methods, especially generative models, hav...
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12/07/2022
One Sample Diffusion Model in Projection Domain for Low-Dose CT Imaging
Low-dose computed tomography (CT) plays a significant role in reducing t...
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11/25/2022
Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction
The radiation dose in computed tomography (CT) examinations is harmful f...
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11/25/2022
Generative Modeling in Structural-Hankel Domain for Color Image Inpainting
In recent years, some researchers focused on using a single image to obt...
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08/15/2022
One-shot Generative Prior Learned from Hankel-k-space for Parallel Imaging Reconstruction
Magnetic resonance imaging serves as an essential tool for clinical diag...
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05/08/2022
WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstruction
Parallel Imaging (PI) is one of the most im-portant and successful devel...
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04/05/2022
Multi-Weight Respecification of Scan-specific Learning for Parallel Imaging
Parallel imaging is widely used in magnetic resonance imaging as an acce...
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03/21/2022
K-space and Image Domain Collaborative Energy based Model for Parallel MRI Reconstruction
Decreasing magnetic resonance (MR) image acquisition times can potential...
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03/18/2022
Rethinking the optimization process for self-supervised model-driven MRI reconstruction
Recovering high-quality images from undersampled measurements is critica...
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01/25/2022
Universal Generative Modeling for Calibration-free Parallel Mr Imaging
The integration of compressed sensing and parallel imaging (CS-PI) provi...
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01/19/2022
Virtual Coil Augmentation Technology for MRI via Deep Learning
Magnetic resonance imaging (MRI) is a widely used medical imaging modali...
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01/19/2022
Variable Augmented Network for Invertible MR Coil Compression
A large number of coils are able to provide enhanced signal-to-noise rat...
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09/26/2021
Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework
Image reconstruction from undersampled k-space data plays an important r...
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09/07/2021
MRI Reconstruction Using Deep Energy-Based Model
Purpose: Although recent deep energy-based generative models (EBMs) have...
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09/02/2021
Variable Augmented Network for Invertible Modality Synthesis-Fusion
As an effective way to integrate the information contained in multiple m...
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08/14/2021
High-dimensional Assisted Generative Model for Color Image Restoration
This work presents an unsupervised deep learning scheme that exploiting ...
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07/09/2021
Wavelet Transform-assisted Adaptive Generative Modeling for Colorization
Unsupervised deep learning has recently demonstrated the promise to prod...
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12/28/2020
Joint Intensity-Gradient Guided Generative Modeling for Colorization
This paper proposes an iterative generative model for solving the automa...
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09/27/2020
Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of Generative Model
Dose reduction in computed tomography (CT) is essential for decreasing r...
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08/14/2020
Homotopic Gradients of Generative Density Priors for MR Image Reconstruction
Deep learning, particularly the generative model, has demonstrated treme...
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10/23/2019
Learning Priors in High-frequency Domain for Inverse Imaging Reconstruction
Ill-posed inverse problems in imaging remain an active research topic in...
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09/24/2019
IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRI
To improve the compressive sensing MRI (CS-MRI) approaches in terms of f...
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09/03/2019
Denoising Auto-encoding Priors in Undecimated Wavelet Domain for MR Image Reconstruction
Compressive sensing is an impressive approach for fast MRI. It aims at r...
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08/24/2019
LANTERN: learn analysis transform network for dynamic magnetic resonance imaging with small dataset
This paper proposes to learn analysis transform network for dynamic magn...
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08/06/2019
Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging
Parallel imaging has been an essential technique to accelerate MR imagin...
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07/16/2019
X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-range Dependencies
The morbidity of brain stroke increased rapidly in the past few years. T...
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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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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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10/26/2018