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 51–75 of 441 papers

TitleStatusHype
HUMUS-Net: Hybrid unrolled multi-scale network architecture for accelerated MRI reconstructionCode1
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical EvaluationCode1
Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image ReconstructionCode1
Federated Learning of Generative Image Priors for MRI ReconstructionCode1
Bayesian MRI Reconstruction with Joint Uncertainty Estimation using Diffusion ModelsCode1
Fast MRI Reconstruction: How Powerful Transformers Are?Code1
ReconFormer: Accelerated MRI Reconstruction Using Recurrent TransformerCode1
Swin Transformer for Fast MRICode1
Assessment of Data Consistency through Cascades of Independently Recurrent Inference Machines for fast and robust accelerated MRI reconstructionCode1
Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI ReconstructionCode1
VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI ReconstructionCode1
Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised LearningCode1
Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training FrameworkCode1
fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI DataCode1
High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching LossCode1
Deep MRI Reconstruction with Radial SubsamplingCode1
Multi-Modal MRI Reconstruction Assisted with Spatial Alignment NetworkCode1
Uncertainty-Guided Progressive GANs for Medical Image TranslationCode1
Data augmentation for deep learning based accelerated MRI reconstruction with limited dataCode1
Task Transformer Network for Joint MRI Reconstruction and Super-ResolutionCode1
Is good old GRAPPA dead?Code1
Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial TransformersCode1
Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating OptimizationCode1
Zero-Shot Self-Supervised Learning for MRI ReconstructionCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
Show:102550
← PrevPage 3 of 18Next →
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