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 101–125 of 441 papers

TitleStatusHype
MambaRecon: MRI Reconstruction with Structured State Space ModelsCode0
MDPG: Multi-domain Diffusion Prior Guidance for MRI ReconstructionCode0
Deep Generative Adversarial Networks for Compressed Sensing Automates MRICode0
Accelerated First Order Methods for Variational ImagingCode0
MAC-ReconNet: A Multiple Acquisition Context based Convolutional Neural Network for MR Image Reconstruction using Dynamic Weight PredictionCode0
Learning Deep MRI Reconstruction Models from Scratch in Low-Data RegimesCode0
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space SubsetsCode0
K-space and Image Domain Collaborative Energy based Model for Parallel MRI ReconstructionCode0
JotlasNet: Joint Tensor Low-Rank and Attention-based Sparse Unrolling Network for Accelerating Dynamic MRICode0
Inference Stage Denoising for Undersampled MRI ReconstructionCode0
A Deep Learning Approach Using Masked Image Modeling for Reconstruction of Undersampled K-spacesCode0
Coupled Dictionary Learning for Multi-contrast MRI ReconstructionCode0
Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI ReconstructionCode0
Convergent Complex Quasi-Newton Proximal Methods for Gradient-Driven Denoisers in Compressed Sensing MRI ReconstructionCode0
Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion ModelsCode0
Deep Geometric Distillation Network for Compressive Sensing MRICode0
HyperCoil-Recon: A Hypernetwork-based Adaptive Coil Configuration Task Switching Network for MRI ReconstructionCode0
Deep-learning-based acceleration of MRI for radiotherapy planning of pediatric patients with brain tumorsCode0
LMO: Linear Mamba Operator for MRI ReconstructionCode0
MRI Recovery with Self-Calibrated Denoisers without Fully-Sampled DataCode0
Deep Learning-based MRI Reconstruction with Artificial Fourier Transform Network (AFTNet)Code0
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine ImagingCode0
CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI ReconstructionCode0
An unsupervised method for MRI recovery: Deep image prior with structured sparsityCode0
An Unsupervised Deep Learning Method for Multi-coil Cine MRICode0
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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