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
A Comprehensive Survey on Magnetic Resonance Image Reconstruction	Mar 10, 2025	DiagnosticImage Reconstruction	—Unverified
Deep Learning for Accelerated and Robust MRI Reconstruction: a Review	Apr 24, 2024	Deep LearningDiagnostic	—Unverified
A Scale Invariant Approach for Sparse Signal Recovery	Dec 20, 2018	MRI Reconstruction	—Unverified
Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction	Apr 1, 2019	BIG-bench Machine Learningcompressed sensing	—Unverified
D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction	Mar 25, 2025	MRI ReconstructionSelf-Supervised Learning	—Unverified
Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstruction	Dec 13, 2024	DenoisingMRI Reconstruction	—Unverified
A review and experimental evaluation of deep learning methods for MRI reconstruction	Sep 17, 2021	compressed sensingDeep Learning	—Unverified
A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis	May 2, 2022	MRI Reconstruction	—Unverified
Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach	Apr 10, 2024	image-classificationImage Classification	—Unverified
Cross-Modal Vertical Federated Learning for MRI Reconstruction	Jun 5, 2023	DisentanglementFederated Learning	—Unverified

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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