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Accelerating magnetic resonance imaging via deep learning

https://doi.org/10.1109/isbi.2016.7493320
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/mrm.22428openalex-snapshot
SPIRiT: Iterative self‐consistent parallel imaging reconstruction from arbitrary k‐space
inferredcites →https://doi.org/10.1002/mrm.22964openalex-snapshot
Parallel imaging with nonlinear reconstruction using variational penalties
inferredcites →https://doi.org/10.1007/978-3-319-10593-2_13openalex-snapshot
Learning a Deep Convolutional Network for Image Super-Resolution
inferredcites →https://doi.org/10.1016/j.media.2011.11.008openalex-snapshot
Manifold learning for image-based breathing gating in ultrasound and MRI
inferredcites →https://doi.org/10.1109/cvpr.2015.7298854openalex-snapshot
DeepID-Net: Deformable deep convolutional neural networks for object detection
inferredcites →https://doi.org/10.1109/isbi.2007.357020openalex-snapshot
SPATIOTEMPORAL IMAGINGWITH PARTIALLY SEPARABLE FUNCTIONS
inferredcites →https://doi.org/10.1109/isbi.2010.5490076openalex-snapshot
Spatiotemporal imaging with partially separable functions: A matrix recovery approach
inferredcites →https://doi.org/10.1109/nfsi-icfbi.2007.4387720openalex-snapshot
Spatiotemporal Imaging with Partially Separable Functions
inferredcites →https://doi.org/10.1109/tip.2011.2150231openalex-snapshot
Multivariate Compressive Sensing for Image Reconstruction in the Wavelet Domain: Using Scale Mixture Models
inferredcites →https://doi.org/10.1109/tip.2013.2282900openalex-snapshot
Fenchel Duality Based Dictionary Learning for Restoration of Noisy Images
inferredcites →https://doi.org/10.1109/tmi.2003.815896openalex-snapshot
Fast algorithms for GS-model-based image reconstruction in data-sharing fourier imaging
inferredcites →https://doi.org/10.1109/tmi.2010.2073717openalex-snapshot
Computational Acceleration for MR Image Reconstruction in Partially Parallel Imaging
inferredcites →https://doi.org/10.1109/tmi.2010.2088133openalex-snapshot
Fast MR Image Reconstruction for Partially Parallel Imaging With Arbitrary $k$-Space Trajectories
inferredcites →https://doi.org/10.1109/tmi.2010.2100850openalex-snapshot
Accelerated Dynamic MRI Exploiting Sparsity and Low-Rank Structure: k-t SLR
inferredcites →https://doi.org/10.1109/tmi.2013.2256464openalex-snapshot
Highly Undersampled Magnetic Resonance Image Reconstruction Using Two-Level Bregman Method With Dictionary Updating
inferredcites →https://doi.org/10.1109/tpami.2012.59openalex-snapshot
3D Convolutional Neural Networks for Human Action Recognition
inferredcites →https://doi.org/10.1137/100792688openalex-snapshot
Fast Algorithms for Image Reconstruction with Application to Partially Parallel MR Imaging
inferredcites →https://doi.org/10.48550/arxiv.1412.5661openalex-snapshot
DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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DeepSENSE: Learning coil sensitivity functions for SENSE reconstruction using deep learning
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SuperMAP: Deep ultrafast MR relaxometry with joint spatiotemporal undersampling
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Rapid high‐fidelity T2* mapping using single‐shot overlapping‐echo acquisition and deep learning reconstruction
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Bayesian MRI reconstruction with joint uncertainty estimation using diffusion models
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Highly‐accelerated CEST MRI using frequency‐offset‐dependent k‐space sampling and deep‐learning reconstruction
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Multi‐mask self‐supervised learning for physics‐guided neural networks in highly accelerated magnetic resonance imaging
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Universal generative modeling in dual domains for dynamic MRI
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Deep Parallel MRI Reconstruction Network Without Coil Sensitivities
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Deep Cascade Wavelet Network for Compressed Sensing-MRI
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Universal Undersampled MRI Reconstruction
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Self-supervised Learning for MRI Reconstruction with a Parallel Network Training Framework
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Acceleration by Deep-Learnt Sharing of Superfluous Information in Multi-contrast MRI
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MR Image Reconstruction Based on Densely Connected Residual Generative Adversarial Network–DCR-GAN
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Self-supervised Dynamic MRI Reconstruction
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Deep MRI Reconstruction with Generative Vision Transformers
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Undersampled MRI Reconstruction with Side Information-Guided Normalisation
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Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI
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Towards Performant and Reliable Undersampled MR Reconstruction via Diffusion Model Sampling
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Segmentation-Aware MRI Reconstruction
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Cascade Multiscale Swin-Conv Network for Fast MRI Reconstruction
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Semi-supervised Distillation Learning Based on Swin Transformer for MRI Reconstruction
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Efficient MRI Reconstruction with Reinforcement Learning for Automatic Acquisition Stopping
inferred← citeshttps://doi.org/10.1007/978-3-031-27166-3_9openalex-snapshot
Augmented/Virtual Reality and Artificial Intelligence in Dental Education and Research
inferred← citeshttps://doi.org/10.1007/978-3-031-28666-7_6openalex-snapshot
Deep Learning Enhanced Medical Microwave Imaging
inferred← citeshttps://doi.org/10.1007/978-3-031-34048-2_42openalex-snapshot
Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging
inferred← citeshttps://doi.org/10.1007/978-3-031-35197-6_29openalex-snapshot
Deep Learning for Automated Segmentation and Quantitative Mapping with UTE MRI
inferred← citeshttps://doi.org/10.1007/978-3-031-43999-5_47openalex-snapshot
Self-supervised MRI Reconstruction with Unrolled Diffusion Models
inferred← citeshttps://doi.org/10.1007/978-3-031-47401-9_33openalex-snapshot
FedAutoMRI: Federated Neural Architecture Search for MR Image Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-031-47969-4_29openalex-snapshot
When System Model Meets Image Prior: An Unsupervised Deep Learning Architecture for Accelerated Magnetic Resonance Imaging
inferred← citeshttps://doi.org/10.1007/978-3-031-52448-6_31openalex-snapshot
Cardiac MRI Reconstruction from Undersampled K-Space Using Double-Stream IFFT and a Denoising GNA-UNET Pipeline
inferred← citeshttps://doi.org/10.1007/978-3-031-52448-6_40openalex-snapshot
Cine Cardiac MRI Reconstruction Using a Convolutional Recurrent Network with Refinement
inferred← citeshttps://doi.org/10.1007/978-3-031-61846-8_9openalex-snapshot
Machine Learning for Quantitative Magnetic Resonance Image Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-031-67285-9_4openalex-snapshot
Transferable Variational Feedback Network for Vendor Generalization in Accelerated MRI
inferred← citeshttps://doi.org/10.1007/978-3-031-72676-7_1openalex-snapshot
The Growing Application Potential of Machine Learning in Healthcare Systems of Modernity
inferred← citeshttps://doi.org/10.1007/978-3-031-73229-4_17openalex-snapshot
Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling
inferred← citeshttps://doi.org/10.1007/978-3-031-73284-3_20openalex-snapshot
7T-Like T1-Weighted and TOF MRI Synthesis from 3T MRI with Multi-contrast Complementary Deep Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-87756-8_40openalex-snapshot
Dynamic Cardiac MRI Reconstruction via Separate Optimization of K-Space and Hybrid-Domian Spatial-Temporal Feature Fusion
inferred← citeshttps://doi.org/10.1007/978-3-032-04965-0_17openalex-snapshot
Dynamic-Aware Spatio-Temporal Representation Learning for Dynamic MRI Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-032-17734-6_31openalex-snapshot
VTransFormer: A Deep Unrolled Foundation Model for Multi-center Multimodal Accelerated Cardiac MRI Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-032-23344-8_10openalex-snapshot
UltraMR-Enforce: A Unified Ensemble Framework for Enhancement of Ultra-Low-Field MRI
inferred← citeshttps://doi.org/10.1007/978-3-319-59050-9_51openalex-snapshot
A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-319-67558-9_4openalex-snapshot
Accelerated Magnetic Resonance Imaging by Adversarial Neural Network
inferred← citeshttps://doi.org/10.1007/978-3-319-94878-2_15openalex-snapshot
Neurological Diseases
inferred← citeshttps://doi.org/10.1007/978-3-319-95921-4_21openalex-snapshot
MRI Super-Resolution Using Multi-channel Total Variation
inferred← citeshttps://doi.org/10.1007/978-981-15-2848-4_84-1openalex-snapshot
Structural Neuroimaging: From Macroscopic to Microscopic Scales
inferred← citeshttps://doi.org/10.1007/978-981-16-5540-1_84openalex-snapshot
Structural Neuroimaging: From Macroscopic to Microscopic Scales
inferred← citeshttps://doi.org/10.1007/978-981-19-2397-5_42openalex-snapshot
Challenges in Deep Learning Applied to the Knee Joint Magnetic Resonance Imaging: A Survey
inferred← citeshttps://doi.org/10.1007/978-981-99-9239-3_53openalex-snapshot
Cooling Performance Elevation of a 3T Animal Gradient Assembly with Hollow Pipe Axial Gradient Coil
inferred← citeshttps://doi.org/10.1007/s00247-021-05057-0openalex-snapshot
Current and emerging artificial intelligence applications for pediatric abdominal imaging
inferred← citeshttps://doi.org/10.1007/s00256-019-03284-zopenalex-snapshot
Current applications and future directions of deep learning in musculoskeletal radiology
inferred← citeshttps://doi.org/10.1007/s00256-021-03876-8openalex-snapshot
AI musculoskeletal clinical applications: how can AI increase my day-to-day efficiency?
inferred← citeshttps://doi.org/10.1007/s00256-022-04008-6openalex-snapshot
Evaluation of a deep learning method for the automated detection of supraspinatus tears on MRI
inferred← citeshttps://doi.org/10.1007/s00256-024-04634-2openalex-snapshot
Modern acceleration in musculoskeletal MRI: applications, implications, and challenges
inferred← citeshttps://doi.org/10.1007/s00259-019-04468-4openalex-snapshot
PET image denoising using unsupervised deep learning
inferred← citeshttps://doi.org/10.1007/s00330-023-09417-2openalex-snapshot
Free-breathing and instantaneous abdominal T2 mapping via single-shot multiple overlapping-echo acquisition and deep learning reconstruction
inferred← citeshttps://doi.org/10.1007/s00330-024-10771-yopenalex-snapshot
Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics
inferred← citeshttps://doi.org/10.1007/s00371-020-02054-6openalex-snapshot
K sparse autoencoder-based accelerated reconstruction of magnetic resonance imaging
inferred← citeshttps://doi.org/10.1007/s00371-025-04302-zopenalex-snapshot
Enhancing MR image super-resolution with a multi-head attention network: capturing high-dimensional medical features
inferred← citeshttps://doi.org/10.1007/s00414-020-02465-zopenalex-snapshot
Automated age estimation of young individuals based on 3D knee MRI using deep learning
inferred← citeshttps://doi.org/10.1007/s10044-021-01006-7openalex-snapshot
Iterative feature refinement with network-driven prior for image restoration
inferred← citeshttps://doi.org/10.1007/s10278-024-01057-2openalex-snapshot
Feature Fusion for Multi-Coil Compressed MR Image Reconstruction
inferred← citeshttps://doi.org/10.1007/s10278-024-01250-3openalex-snapshot
PixCUE: Joint Uncertainty Estimation and Image Reconstruction in MRI using Deep Pixel Classification
inferred← citeshttps://doi.org/10.1007/s10278-026-02089-6openalex-snapshot
Complex-valued Multi-scale Hybrid Attention Network for Fast MRI via Sparsified Data Learning
inferred← citeshttps://doi.org/10.1007/s10334-023-01142-7openalex-snapshot
Improved reconstruction for highly accelerated propeller diffusion 1.5 T clinical MRI
inferred← citeshttps://doi.org/10.1007/s10334-024-01173-8openalex-snapshot
Deep learning for accelerated and robust MRI reconstruction
inferred← citeshttps://doi.org/10.1007/s10334-024-01222-2openalex-snapshot
Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction
inferred← citeshttps://doi.org/10.1007/s10334-025-01274-yopenalex-snapshot
Self-supervised learning for MRI reconstruction: a review and new perspective
inferred← citeshttps://doi.org/10.1007/s10334-026-01362-7openalex-snapshot
Multi-contrast dual-resolution UTE for myelin fraction mapping and structural imaging
inferred← citeshttps://doi.org/10.1007/s10462-020-09861-2openalex-snapshot
Deep learning for biomedical image reconstruction: a survey
inferred← citeshttps://doi.org/10.1007/s10462-022-10259-5openalex-snapshot
Deep learning for compressive sensing: a ubiquitous systems perspective
inferred← citeshttps://doi.org/10.1007/s10489-021-03092-wopenalex-snapshot
Edge-enhanced dual discriminator generative adversarial network for fast MRI with parallel imaging using multi-view information
inferred← citeshttps://doi.org/10.1007/s10489-024-06008-6openalex-snapshot
A multi-domain feature alignment and hierarchical cross feature enhancement network for under-sampled magnetic image reconstruction
inferred← citeshttps://doi.org/10.1007/s10851-025-01236-yopenalex-snapshot
CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping
inferred← citeshttps://doi.org/10.1007/s10851-025-01241-1openalex-snapshot
Efficient Model-Based Deep Learning via Network Pruning and Fine-Tuning
inferred← citeshttps://doi.org/10.1007/s11042-022-12316-1openalex-snapshot
A multi-sequences MRI deep framework study applied to glioma classfication
inferred← citeshttps://doi.org/10.1007/s11263-025-02378-7openalex-snapshot
Deep Convolutional Neural Network Enhanced Non-uniform Fast Fourier Transform for Undersampled MRI Reconstruction
inferred← citeshttps://doi.org/10.1007/s11427-019-1556-7openalex-snapshot
Artificial intelligence in computer-aided diagnosis of abdomen diseases
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