SOTAVerified

MRI Reconstruction

In its most basic form, MRI reconstruction consists in retrieving a complex-valued image from its under-sampled Fourier coefficients. Besides, it can be addressed as a encoder-decoder task, in which the normative model in the latent space will only capture the relevant information without noise or corruptions. Then, we decode the latent space in order to have a reconstructed MRI.

Papers

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Showing 201–250 of 441 papers

TitleStatusHype
Dynamic MRI reconstruction using low-rank plus sparse decomposition with smoothness regularization—0
Data and Physics driven Deep Learning Models for Fast MRI Reconstruction: Fundamentals and Methodologies—0
Deep Learning-based Intraoperative MRI Reconstruction—0
NLCG-Net: A Model-Based Zero-Shot Learning Framework for Undersampled Quantitative MRI ReconstructionCode0
Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems—0
Deep Unfolding Network with Spatial Alignment for multi-modal MRI reconstruction—0
Deep Learning-based MRI Reconstruction with Artificial Fourier Transform Network (AFTNet)Code0
Towards Architecture-Agnostic Untrained Network Priors for Image Reconstruction with Frequency RegularizationCode0
Robust MRI Reconstruction by Smoothed Unrolling (SMUG)Code0
Dual-Domain Multi-Contrast MRI Reconstruction with Synthesis-based Fusion Network—0
Deep Image prior with StruCtUred Sparsity (DISCUS) for dynamic MRI reconstruction—0
Unsupervised Adaptive Implicit Neural Representation Learning for Scan-Specific MRI Reconstruction—0
SubZero: Subspace Zero-Shot MRI ReconstructionCode0
Joint Supervised and Self-supervised Learning for MRI Reconstruction—0
Volumetric Reconstruction Resolves Off-Resonance Artifacts in Static and Dynamic PROPELLER MRICode0
Deep-learning-based acceleration of MRI for radiotherapy planning of pediatric patients with brain tumorsCode0
Fast Controllable Diffusion Models for Undersampled MRI ReconstructionCode0
Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR ImagesCode0
Robust Depth Linear Error Decomposition with Double Total Variation and Nuclear Norm for Dynamic MRI Reconstruction—0
Implicit Representation of GRAPPA Kernels for Fast MRI Reconstruction—0
JSMoCo: Joint Coil Sensitivity and Motion Correction in Parallel MRI with a Self-Calibrating Score-Based Diffusion Model—0
Deep Cardiac MRI Reconstruction with ADMM—0
Multi-scale MRI reconstruction via dilated ensemble networks—0
Score-based Diffusion Models With Self-supervised Learning For Accelerated 3D Multi-contrast Cardiac Magnetic Resonance Imaging—0
NoSENSE: Learned unrolled cardiac MRI reconstruction without explicit sensitivity mapsCode0
Unveiling Fairness Biases in Deep Learning-Based Brain MRI ReconstructionCode0
Cine cardiac MRI reconstruction using a convolutional recurrent network with refinementCode0
Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer—0
Convex Latent-Optimized Adversarial Regularizers for Imaging Inverse Problems—0
A plug-and-play synthetic data deep learning for undersampled magnetic resonance image reconstruction—0
Efficient MRI Parallel Imaging Reconstruction by K-Space Rendering via Generalized Implicit Neural RepresentationCode0
Robust Physics-based Deep MRI Reconstruction Via Diffusion PurificationCode0
Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI ReconstructionCode0
Diffusion Modeling with Domain-conditioned Prior Guidance for Accelerated MRI and qMRI Reconstruction—0
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited DataCode0
Federated Pseudo Modality Generation for Incomplete Multi-Modal MRI Reconstruction—0
Two-and-a-half Order Score-based Model for Solving 3D Ill-posed Inverse ProblemsCode0
The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning—0
HyperCoil-Recon: A Hypernetwork-based Adaptive Coil Configuration Task Switching Network for MRI ReconstructionCode0
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space SubsetsCode0
Uncertainty Estimation and Propagation in Accelerated MRI ReconstructionCode0
One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI ReconstructionCode0
Generalizing Supervised Deep Learning MRI Reconstruction to Multiple and Unseen Contrasts using Meta-Learning HypernetworksCode0
A Motion Assessment Method for Reference Stack Selection in Fetal Brain MRI Reconstruction Based on Tensor Rank ApproximationCode0
Encoding Enhanced Complex CNN for Accurate and Highly Accelerated MRI—0
Attention Hybrid Variational Net for Accelerated MRI Reconstruction—0
Brain Anatomy Prior Modeling to Forecast Clinical Progression of Cognitive Impairment with Structural MRICode0
CAMP-Net: Consistency-Aware Multi-Prior Network for Accelerated MRI ReconstructionCode0
PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI ReconstructionCode0
Cross-Modal Vertical Federated Learning for MRI Reconstruction—0
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All datasetsfastMRI Knee 8xfastMRI Knee Val 8xfastMRI Brain 4xfastMRI Brain 8xfastMRI Knee 4xIXI

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HUMUS-Net (train+val data)SSIM0.89—Unverified
2HUMUS-Net (train only)SSIM0.89—Unverified
3End-to-end variational networkSSIM0.89—Unverified
4XPDNetSSIM0.89—Unverified
#ModelMetricClaimedVerifiedStatus
1PromptMRSSIM0.9—Unverified
2HUMUS-Net-LSSIM0.9—Unverified
3HUMUS-NetSSIM0.89—Unverified
4E2E-VarNet (train+val)SSIM0.89—Unverified
#ModelMetricClaimedVerifiedStatus
1End-to-end variational networkSSIM0.96—Unverified
2XPDNetSSIM0.96—Unverified
#ModelMetricClaimedVerifiedStatus
1End-to-end variational networkSSIM0.94—Unverified
2XPDNetSSIM0.94—Unverified
#ModelMetricClaimedVerifiedStatus
1End-to-end variational networkSSIM0.93—Unverified
2XPDNetSSIM0.93—Unverified
#ModelMetricClaimedVerifiedStatus
1Residual U-NETDSSIM0—Unverified