Awesome-MRI-Reconstruction
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Papers
Review
- Deep learning for fast MR imaging: a review for learning reconstruction from incomplete k-space data [paper]
- Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks [paper]
- AI-Based Reconstruction for Fast MRI—A Systematic Review and Meta-Analysis [paper]
- Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction [paper]
Tutorials
- MRI acquisition & image reconstruction tutorial [code]
arXiv papers
- Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction [paper]
- Dual-Domain Reconstruction Networks with V-Net and K-Net for fast MRI [paper]
- Fast MRI Reconstruction: How Powerful Transformers Are? [paper]
- Swin Transformer for Fast MRI [paper] [code]
- Federated Learning of Generative Image Priors for MRI Reconstruction [paper]
- Contrastive Learning for Local and Global Learning MRI Reconstruction [paper]
- Equilibrated Zeroth-Order Unrolled Deep Networks for Accelerated MRI [paper]
- Specificity-Preserving Federated Learning for MR Image Reconstruction [paper]
- Learned Half-Quadratic Splitting Network for Magnetic Resonance Image Reconstruction [paper]
- MRI Reconstruction Using Deep Energy-Based Model [paper] [Submited to Magnetic Resonance in Medicine]
- High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss [paper] [code] [Submited to Magnetic Resonance in Medicine]
- Multi-Modal MRI Reconstruction Assisted with Spatial Alignment Network [paper] [code]
- Deep MRI Reconstruction with Radial Subsampling [paper] [code]
- Multi-Modal MRI Reconstruction with Spatial Alignment Network [paper] [code]
- Accelerated Multi-Modal MR Imaging with Transformers [paper] [code]
- Accelerated MRI Reconstruction with Separable and Enhanced Low-Rank Hankel Regularization [paper]
- Joint Calibrationless Reconstruction and Segmentation of Parallel MRI [paper]
- Adaptive Gradient Balancing for Undersampled MRI Reconstruction and Image-to-Image Translation [paper]
- Zero-Shot Self-Supervised Learning for MRI Reconstruction [paper]
- Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks [paper] [code]
- Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformers [paper]
2022
- Joint Reconstruction of Vascular Structure and Function Maps in Dynamic Contrast Enhanced MRI Using Vascular Heterogeneity Priors (TMI) [paper]
- Spatiotemporal Flexible Sparse Reconstruction for Rapid Dynamic Contrast-Enhanced MRI (TBE) []paper]
- Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas (MedIA)[paper]
- IDPCNN: Iterative denoising and projecting CNN for MRI reconstruction (J. CAM) [paper]
- Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks (CVPR) [paper]
- Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution (CVPR) [paper] [code]
- Vox2Cortex: Fast Explicit Reconstruction of Cortical Surfaces from 3D MRI Scans with Geometric Deep Neural Networks (CVPR) [paper]
- 2D probabilistic undersampling pattern optimization for MR image reconstruction (MedIA) [paper]
- Sampling possible reconstructions of undersampled acquisitions in MR imaging with a deep learned prior (TMI) [paper]
- Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformers (TMI) [paper]
- Pyramid Convolutional RNN for MRI Image Reconstruction (TMI) [paper]
- Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction (TMI) [paper]
- Low-Rank and Framelet Based Sparsity Decomposition for Interventional MRI Reconstructionn (TBE) [paper]
- A Plug-and-Play Approach To Multiparametric Quantitative MRI: Image Reconstruction Using Pre-Trained Deep Denoisers (ISBI) [paper]
- LONDN-MRI: Adaptive Local Neighborhood-Based Networks for MR Image Reconstruction from Undersampled Data (ISBI) [paper]
- Leaders: Learnable Deep Radial Subsampling for Mri Reconstruction (ISBI) [paper]
- MPTGAN: A Multimodal Prior-Based Triple-Branch Network for Fast Prostate Mri Reconstruction (ISBI) [paper]
- Dynamic Cardiac MRI Reconstruction Using Combined Tensor Nuclear Norm and Casorati Matrix Nuclear Norm Regularizations (ISBI) [paper]
- Distributed Memory-Efficient Physics-Guided Deep Learning Reconstruction for Large-Scale 3d Non-Cartesian MRI (ISBI) [paper]
- Joint Alignment and Reconstruction of Multislice Dynamic MRI Using Variational Manifold Learning (ISBI) [paper]
- Compressed Sensing MRI Reconstruction with Co-VeGAN: Complex-Valued Generative Adversarial Network (WACV) [paper]
2021
- Robust Compressed Sensing MRI with Deep Generative Priors (NeurIPS) [paper] [code]
- Fine-grained MRI Reconstruction using Attentive Selection Generative Adversarial Networks (ICASSP) [paper]
- Brain MRI super-resolution using coupled-projection residual network (Neurocomputing) [paper]
- Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution (MedIA) [paper]
- Uncertainty Quantification in Deep MRI Reconstruction (TMI)[paper]
- Brain Surface Reconstruction from MRI Images based on Segmentation Networks Applying Signed Distance Maps (ISBI) [paper]
- Density Compensated Unrolled Networks For Non-Cartesian MRI Reconstruction (ISBI) [paper]
- Calibrationless MRI Reconstruction With A Plug-In Denoiser (ISBI) [paper]
- Joint Deep Model-Based MR Image and Coil Sensitivity Reconstruction Network (Joint-ICNet) for Fast MRI (CVPR) [paper]
- Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration Network (MICCAI) [paper] [code]
- Two-Stage Self-Supervised Cycle-Consistency Network for Reconstruction of Thin-Slice MR Images (MICCAI) [paper]
- Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI) [paper] [code]
- Over-and-Under Complete Convolutional RNN for MRI Reconstruction (MICCAI) [paper]
- Universal Undersampled MRI Reconstruction (MICCAI) [paper]
- Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization (MICCAI) [paper] [code]
- Self-supervised Learning for MRI Reconstruction with a Parallel Network Training Framework (MICCAI) [paper] [code]
- Memory-Efficient Learning for High-Dimensional MRI Reconstruction (MICCAI) [paper] [code]
- IREM: High-Resolution Magnetic Resonance Image Reconstruction via Implicit Neural Representation (MICCAI) [paper]
- Fast Magnetic Resonance Imaging on Regions of Interest: From Sensing to Reconstruction (MICCAI) [paper]
- Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction (MICCAI) [paper]
- Generalised Super Resolution for Quantitative MRI Using Self-supervised Mixture of Experts (MICCAI) [paper] [code]
- DA-VSR: Domain Adaptable Volumetric Super-Resolution for Medical Images (MICCAI) [paper]
- Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution (MICCAI) [paper]
- Interpretable Deep Learning for Multimodal Super-Resolution of Medical Images (MICCAI) [paper]
- MRI Super-Resolution Through Generative Degradation Learning (MICCAI) [paper]
- Data augmentation for deep learning based accelerated MRI reconstruction with limited data (ICML) [paper] [code]
- Deep Geometric Distillation Network for Compressive Sensing MRI (IEEE-EMBS BHI oral) [paper] [code]
- Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction (AAAI) [paper code]
- DONet: Dual-Octave Network for Fast MR Image Reconstruction (TNNLS) [paper]
- Adaptive Gradient Balancing for Undersampled MRI Reconstruction and Image-to-Image Translation (ICCP) [paper]
- Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction [paper]
- Systematic evaluation of iterative deep neural networks for fast parallel MRI reconstruction with sensitivity-weighted coil combination [paper]
- Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks [paper] [code]
2020
- DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction with Deep T1 Prior (CVPR) [paper] [code]
- GrappaNet: Combining Parallel Imaging With Deep Learning for Multi-Coil MRI Reconstruction (CVPR) [paper]
- Deep-Learning-Based Optimization of the Under-Sampling Pattern in MRI (TCI) [paper]
- Improving Amide Proton Transfer-Weighted MRI Reconstruction Using T2-Weighted Images (MICCAI) [paper]
- End-to-End Variational Networks for Accelerated MRI Reconstruction (MICCAI) [paper]
- MRI Image Reconstruction via Learning Optimization Using Neural ODEs (MICCAI) [paper]
- Learning a Gradient Guidance for Spatially Isotropic MRI Super-Resolution Reconstruction (MICCAI) [paper]
- Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness (MICCAI) [paper]
- Model-Driven Deep Attention Network for Ultra-fast Compressive Sensing MRI Guided by Cross-contrast MR Image (MICCAI) [paper]
- CDF-Net: Cross-Domain Fusion Network for Accelerated MRI Reconstruction (MICCAI) [paper]
2019
2018
- KIKI-net: cross-domain convolutional neural networks for reconstructing undersampled magnetic resonance images [paper]
- Learning a variational network for reconstruction of accelerated MRI data [paper] [code]
- Bayesian Deep Learning for Accelerated MR Image Reconstruction [paper]
2017
- A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction [paper] [code]
- A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction [paper] [code]