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 171–180 of 441 papers

Title	Date	Tasks	Status
Edge-weighted pFISTA-Net for MRI Reconstruction	Feb 15, 2023	Deep LearningEdge Detection	—Unverified
Equilibrated Zeroth-Order Unrolled Deep Networks for Accelerated MRI	Dec 18, 2021	MRI ReconstructionRolling Shutter Correction	—Unverified
Edge-Enhanced Dual Discriminator Generative Adversarial Network for Fast MRI with Parallel Imaging Using Multi-view Information	Dec 10, 2021	Generative Adversarial NetworkImage Reconstruction	—Unverified
Compressed Sensing MRI via a Multi-scale Dilated Residual Convolution Network	Jun 11, 2019	compressed sensingMRI Reconstruction	—Unverified
Coil Sketching for computationally-efficient MR iterative reconstruction	May 10, 2023	compressed sensingComputational Efficiency	—Unverified
Edge Computing for Physics-Driven AI in Computational MRI: A Feasibility Study	May 30, 2025	Computational EfficiencyEdge-computing	—Unverified
Exploring the Power of Generative Deep Learning for Image-to-Image Translation and MRI Reconstruction: A Cross-Domain Review	Mar 16, 2023	Deep LearningImage-to-Image Translation	—Unverified
MRI Reconstruction with Side Information using Diffusion Models	Mar 26, 2023	AnatomyImage Reconstruction	—Unverified
Dynamic MRI using Learned Transform-based Tensor Low-Rank Network (LT^2LR-Net)	Jun 2, 2022	Image ReconstructionMRI Reconstruction	—Unverified
CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI	Jun 27, 2024	Image ReconstructionMRI Reconstruction	—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