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 211–220 of 441 papers

Title	Date	Tasks	Status
Unsupervised Adaptive Implicit Neural Representation Learning for Scan-Specific MRI Reconstruction	Dec 1, 2023	MRI ReconstructionRepresentation Learning	—Unverified
Dual-Domain Multi-Contrast MRI Reconstruction with Synthesis-based Fusion Network	Dec 1, 2023	MRI Reconstruction	—Unverified
SubZero: Subspace Zero-Shot MRI Reconstruction	Nov 28, 2023	MRI ReconstructionSelf-Supervised Learning	CodeCode Available
Joint Supervised and Self-supervised Learning for MRI Reconstruction	Nov 27, 2023	DiagnosticMRI Reconstruction	—Unverified
Deep-learning-based acceleration of MRI for radiotherapy planning of pediatric patients with brain tumors	Nov 22, 2023	AnatomyDiagnostic	CodeCode Available
Volumetric Reconstruction Resolves Off-Resonance Artifacts in Static and Dynamic PROPELLER MRI	Nov 22, 2023	DiagnosticGPU	CodeCode Available
Fast Controllable Diffusion Models for Undersampled MRI Reconstruction	Nov 20, 2023	MRI Reconstruction	CodeCode Available
Uni-COAL: A Unified Framework for Cross-Modality Synthesis and Super-Resolution of MR Images	Nov 14, 2023	AttributeImage Generation	CodeCode Available
Robust Depth Linear Error Decomposition with Double Total Variation and Nuclear Norm for Dynamic MRI Reconstruction	Oct 23, 2023	compressed sensingMRI Reconstruction	—Unverified
Implicit Representation of GRAPPA Kernels for Fast MRI Reconstruction	Oct 16, 2023	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