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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–175 of 441 papers

TitleStatusHype
Continuous K-space Recovery Network with Image Guidance for Fast MRI Reconstruction—0
An All-in-one Approach for Accelerated Cardiac MRI Reconstruction—0
On the Foundation Model for Cardiac MRI Reconstruction—0
A Learned Proximal Alternating Minimization Algorithm and Its Induced Network for a Class of Two-block Nonconvex and Nonsmooth Optimization—0
Benchmarking 3D multi-coil NC-PDNet MRI reconstruction—0
Zero-shot Dynamic MRI Reconstruction with Global-to-local Diffusion ModelCode0
Sub-DM:Subspace Diffusion Model with Orthogonal Decomposition for MRI ReconstructionCode0
LDPM: Towards undersampled MRI reconstruction with MR-VAE and Latent Diffusion Prior—0
Robust plug-and-play methods for highly accelerated non-Cartesian MRI reconstruction—0
Deep Multi-contrast Cardiac MRI Reconstruction via vSHARP with Auxiliary Refinement Network—0
MS-Glance: Bio-Insipred Non-semantic Context Vectors and their Applications in Supervising Image ReconstructionCode0
SGD Jittering: A Training Strategy for Robust and Accurate Model-Based Architectures—0
Fully Unsupervised Dynamic MRI Reconstruction via Diffeo-Temporal EquivarianceCode0
A Unified Model for Compressed Sensing MRI Across Undersampling Patterns—0
Sampling-Pattern-Agnostic MRI Reconstruction through Adaptive Consistency Enforcement with Diffusion Model—0
A Plug-and-Play Method for Guided Multi-contrast MRI Reconstruction based on Content/Style Modeling—0
MambaRecon: MRI Reconstruction with Structured State Space ModelsCode0
Joint PET-MRI Reconstruction with Diffusion Stochastic Differential Model—0
MR Optimized Reconstruction of Simultaneous Multi-Slice Imaging Using Diffusion Model—0
Robust Simultaneous Multislice MRI Reconstruction Using Deep Generative PriorsCode0
Segmentation-guided MRI reconstruction for meaningfully diverse reconstructionsCode0
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine ImagingCode0
MMR-Mamba: Multi-Modal MRI Reconstruction with Mamba and Spatial-Frequency Information Fusion—0
CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRICode0
ALMA: a mathematics-driven approach for determining tuning parameters in generalized LASSO problems, with applications to MRI—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