{"total":45,"rows":[{"id":"2103.02148","title":"Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning","created":"2021-03-03","cited_by_count":78,"area":null},{"id":"2105.08059","title":"Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformers","created":"2021-05-15","cited_by_count":77,"area":null},{"id":"2106.14248","title":"Multi-Modal Transformer for Accelerated MR Imaging","created":"2021-06-27","cited_by_count":43,"area":null},{"id":"2112.12744","title":"AI-based Reconstruction for Fast MRI -- A Systematic Review and Meta-analysis","created":"2021-12-23","cited_by_count":38,"area":null},{"id":"2209.01725","title":"Imaging with Equivariant Deep Learning","created":"2022-09-05","cited_by_count":35,"area":null},{"id":"2106.08886","title":"Over-and-Under Complete Convolutional RNN for MRI Reconstruction","created":"2021-06-16","cited_by_count":29,"area":null},{"id":"2106.14947","title":"Data augmentation for deep learning based accelerated MRI reconstruction with limited data","created":"2021-06-28","cited_by_count":20,"area":null},{"id":"2204.03804","title":"A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesis","created":"2022-04-08","cited_by_count":16,"area":null},{"id":"2109.08618","title":"A review and experimental evaluation of deep learning methods for MRI reconstruction","created":"2021-09-17","cited_by_count":13,"area":null},{"id":"2104.05345","title":"Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction","created":"2021-04-12","cited_by_count":12,"area":null},{"id":"2105.05980","title":"DONet: Dual-Octave Network for Fast MR Image Reconstruction","created":"2021-05-12","cited_by_count":9,"area":null},{"id":"2202.01494","title":"PARCEL: Physics-based Unsupervised Contrastive Representation Learning for Multi-coil MR Imaging","created":"2022-02-03","cited_by_count":8,"area":null},{"id":"2412.09331","title":"Physics-Driven Autoregressive State Space Models for Medical Image Reconstruction","created":"2024-12-12","cited_by_count":8,"area":null},{"id":"2308.02958","title":"K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets","created":"2023-08-05","cited_by_count":6,"area":null},{"id":"2103.09203","title":"ReconResNet: Regularised Residual Learning for MR Image Reconstruction of Undersampled Cartesian and Radial Data","created":"2021-03-16","cited_by_count":4,"area":null},{"id":"2105.01800","title":"Generative Adversarial Networks (GAN) Powered Fast Magnetic Resonance Imaging -- Mini Review, Comparison and Perspectives","created":"2021-05-04","cited_by_count":3,"area":null},{"id":"2204.08528","title":"An Optimal Time Variable Learning Framework for Deep Neural Networks","created":"2022-04-18","cited_by_count":3,"area":null},{"id":"2303.12735","title":"SMUG: Towards robust MRI reconstruction by smoothed unrolling","created":"2023-03-14","cited_by_count":3,"area":null},{"id":"2304.02883","title":"GA-HQS: MRI reconstruction via a generically accelerated unfolding approach","created":"2023-04-06","cited_by_count":3,"area":null},{"id":"2304.11400","title":"Fast MRI Reconstruction via Edge Attention","created":"2023-04-22","cited_by_count":3,"area":null},{"id":"2304.12507","title":"Learning Task-Specific Strategies for Accelerated MRI","created":"2023-04-25","cited_by_count":3,"area":null},{"id":"2306.11238","title":"CAMP-Net: Consistency-Aware Multi-Prior Network for Accelerated MRI Reconstruction","created":"2023-06-20","cited_by_count":3,"area":null},{"id":"2306.11977","title":"Encoding Enhanced Complex CNN for Accurate and Highly Accelerated MRI","created":"2023-06-21","cited_by_count":3,"area":null},{"id":"2405.02958","title":"Score-based Generative Priors Guided Model-driven Network for MRI Reconstruction","created":"2024-05-05","cited_by_count":3,"area":null},{"id":"2203.09724","title":"Rethinking the optimization process for self-supervised model-driven MRI reconstruction","created":"2022-03-18","cited_by_count":2,"area":null},{"id":"2204.01706","title":"Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers","created":"2022-04-01","cited_by_count":2,"area":null},{"id":"2207.02073","title":"A Densely Interconnected Network for Deep Learning Accelerated MRI","created":"2022-07-05","cited_by_count":2,"area":null},{"id":"2306.02886","title":"Image Reconstruction for Accelerated MR Scan with Faster Fourier Convolutional Neural Networks","created":"2023-06-05","cited_by_count":2,"area":null},{"id":"2608.14422","title":"UMPIRE-Net: Unrolled Magnitude-Phase Regularization Network for Accelerated MRI","created":"2026-08-14","cited_by_count":2,"area":null},{"id":"2206.07364","title":"Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction","created":"2022-06-15","cited_by_count":1,"area":null},{"id":"2301.01355","title":"Holistic Multi-Slice Framework for Dynamic Simultaneous Multi-Slice MRI Reconstruction","created":"2023-01-03","cited_by_count":1,"area":null},{"id":"2303.04968","title":"Reconstruction of Cardiac Cine MRI Using Motion-Guided Deformable Alignment and Multi-Resolution Fusion","created":"2023-03-09","cited_by_count":1,"area":null},{"id":"2303.10611","title":"Rethinking Dual-Domain Undersampled MRI reconstruction: domain-specific design from the perspective of the receptive field","created":"2023-03-19","cited_by_count":1,"area":null},{"id":"2309.13385","title":"Cine cardiac MRI reconstruction using a convolutional recurrent network with refinement","created":"2023-09-23","cited_by_count":1,"area":null},{"id":"2407.03034","title":"Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging","created":"2024-07-03","cited_by_count":1,"area":null},{"id":"2411.11282","title":"Continuous K-space Recovery Network with Image Guidance for Fast MRI Reconstruction","created":"2024-11-18","cited_by_count":1,"area":null},{"id":"2601.02141","title":"Efficient Unrolled Networks for Large-Scale 3D Inverse Problems","created":"2026-01-05","cited_by_count":1,"area":null},{"id":"2104.00325","title":"High-quality Low-dose CT Reconstruction Using Convolutional Neural Networks with Spatial and Channel Squeeze and Excitation","created":"2021-04-01","cited_by_count":0,"area":null},{"id":"2205.01673","title":"A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis","created":"2022-05-02","cited_by_count":0,"area":null},{"id":"2206.07280","title":"ERNAS: An Evolutionary Neural Architecture Search for Magnetic Resonance Image Reconstructions","created":"2022-06-15","cited_by_count":0,"area":null},{"id":"2212.02190","title":"L2SR: Learning to Sample and Reconstruct for Accelerated MRI via Reinforcement Learning","created":"2022-12-05","cited_by_count":0,"area":null},{"id":"2304.08072","title":"Two-stage MR Image Segmentation Method for Brain Tumors based on Attention Mechanism","created":"2023-04-17","cited_by_count":0,"area":null},{"id":"2407.03308","title":"Accelerated Proton Resonance Frequency-based Magnetic Resonance Thermometry by Optimized Deep Learning Method","created":"2024-07-03","cited_by_count":0,"area":null},{"id":"2409.15608","title":"Deep Learning Approach for Knee Point Detection on Noisy Data","created":"2024-09-23","cited_by_count":0,"area":null},{"id":"2601.09316","title":"Frequency Error-Guided Under-sampling Optimization for Multi-Contrast MRI Reconstruction","created":"2026-01-14","cited_by_count":0,"area":null}],"next_cursor":null}