- Deep learning for fast MR imaging: a review for learning reconstruction from incomplete k-space data [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]
- Low-Rank and Framelet Based Sparsity Decomposition for Interventional MRI Reconstruction [paper]
- Two-Stage Self-Supervised Cycle-Consistency Network for Reconstruction of Thin-Slice MR Images [paper]
- Memory-efficient Learning for High-Dimensional MRI Reconstruction [paper]
- Joint Calibrationless Reconstruction and Segmentation of Parallel MRI [paper]
- Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction [paper]
- Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization [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]
- 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]
- 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]
- 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]
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