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 191–200 of 441 papers

Title	Date	Tasks	Status	Score
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction	Jul 18, 2022	MRI Reconstruction	CodeCode Available	5
Motion Compensated Dynamic MRI Reconstruction with Local Affine Optical Flow Estimation	Jul 22, 2017	compressed sensingImage Reconstruction	CodeCode Available	5
Self-Supervised Learning of Physics-Guided Reconstruction Neural Networks without Fully-Sampled Reference Data	Dec 16, 2019	compressed sensingMRI Reconstruction	CodeCode Available	5
Self-supervised feature learning for cardiac Cine MR image reconstruction	May 29, 2025	Image ReconstructionMRI Reconstruction	CodeCode Available	5
Deep MRI Reconstruction: Unrolled Optimization Algorithms Meet Neural Networks	Jul 26, 2019	Deep LearningImage Reconstruction	—Unverified	0
Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction	Apr 1, 2019	BIG-bench Machine Learningcompressed sensing	—Unverified	0
Deep learning for undersampled MRI reconstruction	Sep 8, 2017	Deep LearningMRI Reconstruction	—Unverified	0
Deep Learning for Accelerated and Robust MRI Reconstruction: a Review	Apr 24, 2024	Deep LearningDiagnostic	—Unverified	0
Deep Learning-based Intraoperative MRI Reconstruction	Jan 23, 2024	Deep LearningDiagnostic	—Unverified	0
Deep Learning-based Diffusion Tensor Cardiac Magnetic Resonance Reconstruction: A Comparison Study	Mar 31, 2023	MRI Reconstruction	—Unverified	0

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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