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 131–140 of 441 papers

Title	Date	Tasks	Status	Score
An unsupervised method for MRI recovery: Deep image prior with structured sparsity	Jan 2, 2025	compressed sensingImage Reconstruction	CodeCode Available	5
An Unsupervised Deep Learning Method for Multi-coil Cine MRI	Dec 20, 2019	Deep LearningMRI Reconstruction	CodeCode Available	5
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction	May 25, 2023	MRI Reconstruction	CodeCode Available	5
Inference Stage Denoising for Undersampled MRI Reconstruction	Feb 12, 2024	Data AugmentationDenoising	CodeCode Available	5
An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities	Sep 20, 2021	Image ReconstructionMRI Reconstruction	CodeCode Available	5
JotlasNet: Joint Tensor Low-Rank and Attention-based Sparse Unrolling Network for Accelerating Dynamic MRI	Feb 17, 2025	MRI Reconstruction	CodeCode Available	5
Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models	May 13, 2025	DenoisingMRI Reconstruction	CodeCode Available	5
Compressed Sensing MRI Reconstruction using a Generative Adversarial Network with a Cyclic Loss	Sep 3, 2017	compressed sensingGenerative Adversarial Network	CodeCode Available	5
Compressed MRI Reconstruction Exploiting a Rotation-Invariant Total Variation Discretization	Nov 26, 2019	Image ReconstructionMRI 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