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 361–370 of 441 papers

Title	Date	Tasks	Status
ERNAS: An Evolutionary Neural Architecture Search for Magnetic Resonance Image Reconstructions	Jun 15, 2022	MRI ReconstructionNeural Architecture Search	—Unverified
Exploring Siamese Networks in Self-Supervised Fast MRI Reconstruction	Jan 18, 2025	MRI ReconstructionSelf-Supervised Learning	—Unverified
Exploring the Power of Generative Deep Learning for Image-to-Image Translation and MRI Reconstruction: A Cross-Domain Review	Mar 16, 2023	Deep LearningImage-to-Image Translation	—Unverified
Fast Multi-class Dictionaries Learning with Geometrical Directions in MRI Reconstruction	Mar 10, 2015	Dictionary LearningImage Reconstruction	—Unverified
Fast T2w/FLAIR MRI Acquisition by Optimal Sampling of Information Complementary to Pre-acquired T1w MRI	Nov 11, 2021	MRI Reconstruction	—Unverified
Federated Pseudo Modality Generation for Incomplete Multi-Modal MRI Reconstruction	Aug 20, 2023	Federated LearningMRI Reconstruction	—Unverified
From Coarse to Continuous: Progressive Refinement Implicit Neural Representation for Motion-Robust Anisotropic MRI Reconstruction	Jun 19, 2025	MRI Reconstruction	—Unverified
GA-HQS: MRI reconstruction via a generically accelerated unfolding approach	Apr 6, 2023	compressed sensingMRI Reconstruction	—Unverified
Generalising Deep Learning MRI Reconstruction across Different Domains	Jan 31, 2019	Deep LearningMRI Reconstruction	—Unverified
Generative Adversarial Networks (GAN) Powered Fast Magnetic Resonance Imaging -- Mini Review, Comparison and Perspectives	May 4, 2021	Compressive SensingMRI Reconstruction	—Unverified

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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