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
Learning Deep MRI Reconstruction Models from Scratch in Low-Data Regimes	Jan 6, 2023	DiagnosticMRI Reconstruction	CodeCode Available
VS-Net: Variable splitting network for accelerated parallel MRI reconstruction	Jul 19, 2019	compressed sensingDeep Learning	CodeCode Available
Fully Unsupervised Dynamic MRI Reconstruction via Diffeo-Temporal Equivariance	Oct 11, 2024	MRI Reconstruction	CodeCode Available
Fine-tuning deep learning model parameters for improved super-resolution of dynamic MRI with prior-knowledge	Feb 4, 2021	MRI ReconstructionSSIM	CodeCode Available
Fine-grained MRI Reconstruction using Attentive Selection Generative Adversarial Networks	Mar 13, 2021	compressed sensingDeep Learning	CodeCode Available
Convergent Complex Quasi-Newton Proximal Methods for Gradient-Driven Denoisers in Compressed Sensing MRI Reconstruction	May 7, 2025	compressed sensingDenoising	CodeCode Available
Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition	Feb 8, 2019	MRI Reconstruction	CodeCode Available
LMO: Linear Mamba Operator for MRI Reconstruction	Jan 1, 2025	MambaMRI Reconstruction	CodeCode Available
Sub-DM:Subspace Diffusion Model with Orthogonal Decomposition for MRI Reconstruction	Nov 6, 2024	Image ReconstructionMRI Reconstruction	CodeCode Available
CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI Reconstruction	Jun 1, 2023	AnatomyContrastive Learning	CodeCode Available

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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