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 341–350 of 441 papers

Title	Date	Tasks	Status
Dual-domain Multi-path Self-supervised Diffusion Model for Accelerated MRI Reconstruction	Mar 24, 2025	DiagnosticMRI Reconstruction	—Unverified
Dual-Domain Self-Supervised Learning for Accelerated Non-Cartesian MRI Reconstruction	Feb 18, 2023	MRI ReconstructionSelf-Supervised Learning	—Unverified
Rethinking Dual-Domain Undersampled MRI reconstruction: domain-specific design from the perspective of the receptive field	Mar 19, 2023	Deep LearningLayout Design	—Unverified
DuDoUniNeXt: Dual-domain unified hybrid model for single and multi-contrast undersampled MRI reconstruction	Mar 8, 2024	MRI Reconstruction	—Unverified
Dynamic-Aware Spatio-temporal Representation Learning for Dynamic MRI Reconstruction	Jan 15, 2025	MRI ReconstructionRepresentation Learning	—Unverified
Computationally Efficient 3D MRI Reconstruction with Adaptive MLP	Jan 21, 2023	3D ReconstructionGPU	—Unverified
Dynamic MRI reconstruction using low-rank plus sparse decomposition with smoothness regularization	Jan 30, 2024	MRI Reconstruction	—Unverified
Dynamic MRI using Learned Transform-based Tensor Low-Rank Network (LT^2LR-Net)	Jun 2, 2022	Image ReconstructionMRI Reconstruction	—Unverified
Edge Computing for Physics-Driven AI in Computational MRI: A Feasibility Study	May 30, 2025	Computational EfficiencyEdge-computing	—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

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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