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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 71–80 of 441 papers

Title	Date	Tasks	Status	Hype
End-to-End Variational Networks for Accelerated MRI Reconstruction	Apr 14, 2020	Anatomycompressed sensing	CodeCode Available	1
Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems	Mar 10, 2023	CT ReconstructionMRI Reconstruction	CodeCode Available	1
Fast MRI Reconstruction: How Powerful Transformers Are?	Jan 23, 2022	Generative Adversarial NetworkMRI Reconstruction	CodeCode Available	1
Accelerated MRI with Un-trained Neural Networks	Jul 6, 2020	compressed sensingDecoder	CodeCode Available	1
Dynamic Cardiac MRI Reconstruction Using Combined Tensor Nuclear Norm and Casorati Matrix Nuclear Norm Regularizations	Jun 2, 2022	Computational EfficiencyMRI Reconstruction	CodeCode Available	1
CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI?	Jun 25, 2023	MRI Reconstruction	CodeCode Available	1
Generative Autoregressive Transformers for Model-Agnostic Federated MRI Reconstruction	Feb 6, 2025	Federated LearningMRI Reconstruction	CodeCode Available	1
Generative Priors for MRI Reconstruction Trained from Magnitude-Only Images Using Phase Augmentation	Aug 4, 2023	compressed sensingMRI Reconstruction	CodeCode Available	1
Accelerated Multi-Contrast MRI Reconstruction via Frequency and Spatial Mutual Learning	Sep 21, 2024	MRI Reconstruction	CodeCode Available	1
High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss	Aug 27, 2021	MRI ReconstructionSSIM	CodeCode Available	1

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All datasets fastMRI Knee 8x fastMRI Knee Val 8x fastMRI Brain 4x fastMRI Brain 8x fastMRI Knee 4x IXI

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	HUMUS-Net (train+val data)	SSIM	0.89	—	Unverified
2	HUMUS-Net (train only)	SSIM	0.89	—	Unverified
3	End-to-end variational network	SSIM	0.89	—	Unverified
4	XPDNet	SSIM	0.89	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PromptMR	SSIM	0.9	—	Unverified
2	HUMUS-Net-L	SSIM	0.9	—	Unverified
3	HUMUS-Net	SSIM	0.89	—	Unverified
4	E2E-VarNet (train+val)	SSIM	0.89	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	End-to-end variational network	SSIM	0.96	—	Unverified
2	XPDNet	SSIM	0.96	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	End-to-end variational network	SSIM	0.94	—	Unverified
2	XPDNet	SSIM	0.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	End-to-end variational network	SSIM	0.93	—	Unverified
2	XPDNet	SSIM	0.93	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Residual U-NET	DSSIM	0	—	Unverified