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 121–130 of 441 papers

Title	Date	Tasks	Status	Score
Deep Learning-based MRI Reconstruction with Artificial Fourier Transform Network (AFTNet)	Dec 18, 2023	MRI Reconstruction	CodeCode Available	5
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging	Jul 3, 2024	Image ReconstructionMRI Reconstruction	CodeCode Available	5
Convergent Complex Quasi-Newton Proximal Methods for Gradient-Driven Denoisers in Compressed Sensing MRI Reconstruction	May 7, 2025	compressed sensingDenoising	CodeCode Available	5
K-space and Image Domain Collaborative Energy based Model for Parallel MRI Reconstruction	Mar 21, 2022	MRI Reconstruction	CodeCode Available	5
CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI Reconstruction	Jun 1, 2023	AnatomyContrastive Learning	CodeCode Available	5
An unsupervised method for MRI recovery: Deep image prior with structured sparsity	Jan 2, 2025	compressed sensingImage Reconstruction	CodeCode Available	5
Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models	May 13, 2025	DenoisingMRI 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
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