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

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Showing 141–150 of 441 papers

Title	Date	Tasks	Status	Score
JotlasNet: Joint Tensor Low-Rank and Attention-based Sparse Unrolling Network for Accelerating Dynamic MRI	Feb 17, 2025	MRI Reconstruction	CodeCode Available	5
Inference Stage Denoising for Undersampled MRI Reconstruction	Feb 12, 2024	Data AugmentationDenoising	CodeCode Available	5
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets	Aug 5, 2023	MRI Reconstruction	CodeCode Available	5
LMO: Linear Mamba Operator for MRI Reconstruction	Jan 1, 2025	MambaMRI Reconstruction	CodeCode Available	5
A Motion Assessment Method for Reference Stack Selection in Fetal Brain MRI Reconstruction Based on Tensor Rank Approximation	Jun 30, 2023	MRI ReconstructionSensitivity	CodeCode Available	5
Cine cardiac MRI reconstruction using a convolutional recurrent network with refinement	Sep 23, 2023	Image Super-ResolutionMRI Reconstruction	CodeCode Available	5
Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models	May 13, 2025	DenoisingMRI Reconstruction	CodeCode Available	5
Cascaded Dilated Dense Network with Two-step Data Consistency for MRI Reconstruction	Dec 1, 2019	compressed sensingMRI Reconstruction	CodeCode Available	5
CAMP-Net: Consistency-Aware Multi-Prior Network for Accelerated MRI Reconstruction	Jun 20, 2023	Image EnhancementImage Reconstruction	CodeCode Available	5
High-dimensional Fast Convolutional Framework (HICU) for Calibrationless MRI	Apr 19, 2020	compressed sensingMRI Reconstruction	CodeCode Available	5

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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