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 391–400 of 441 papers

Title	Date	Tasks	Status
Robust multi-coil MRI reconstruction via self-supervised denoising	Nov 19, 2024	DenoisingMRI Reconstruction	CodeCode Available
MRI Reconstruction Using Deep Energy-Based Model	Sep 7, 2021	Image Generationmodel	CodeCode Available
Robust Physics-based Deep MRI Reconstruction Via Diffusion Purification	Sep 11, 2023	Adversarial DefenseImage Reconstruction	CodeCode Available
Differentiable SVD based on Moore-Penrose Pseudoinverse for Inverse Imaging Problems	Nov 21, 2024	compressed sensingImage Compressed Sensing	CodeCode Available
Denoising Score-Matching for Uncertainty Quantification in Inverse Problems	Nov 16, 2020	DenoisingMRI Reconstruction	CodeCode Available
Compressed Sensing MRI Reconstruction using a Generative Adversarial Network with a Cyclic Loss	Sep 3, 2017	compressed sensingGenerative Adversarial Network	CodeCode Available
Scan‐specific robust artificial‐neural‐networks for k‐space interpolation (RAKI) reconstruction: Database‐free deep learning for fast imaging	Sep 18, 2018	MRI Reconstruction	CodeCode Available
MRI Recovery with Self-Calibrated Denoisers without Fully-Sampled Data	Apr 25, 2023	DenoisingImage Reconstruction	CodeCode Available
Deep Parallel MRI Reconstruction Network Without Coil Sensitivities	Aug 4, 2020	Image ReconstructionMRI Reconstruction	CodeCode Available
Scan-specific Self-supervised Bayesian Deep Non-linear Inversion for Undersampled MRI Reconstruction	Mar 1, 2022	Bayesian Inferencecompressed sensing	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