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 381–390 of 441 papers

Title	Date	Tasks	Status
Synthetic PET via Domain Translation of 3D MRI	Jun 11, 2022	MRI ReconstructionTranslation	CodeCode Available
Structure Preserving Compressive Sensing MRI Reconstruction using Generative Adversarial Networks	Oct 14, 2019	Compressive SensingGenerative Adversarial Network	CodeCode Available
An Interpretable MRI Reconstruction Network with Two-grid-cycle Correction and Geometric Prior Distillation	May 14, 2022	compressed sensingDeep Learning	CodeCode Available
Erase to Enhance: Data-Efficient Machine Unlearning in MRI Reconstruction	May 24, 2024	Image-to-Image TranslationMachine Unlearning	CodeCode Available
Robust MRI Reconstruction by Smoothed Unrolling (SMUG)	Dec 12, 2023	Adversarial Defenseimage-classification	CodeCode Available
Motion Compensated Dynamic MRI Reconstruction with Local Affine Optical Flow Estimation	Jul 22, 2017	compressed sensingImage Reconstruction	CodeCode Available
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging	Jul 3, 2024	Image ReconstructionMRI Reconstruction	CodeCode Available
A Trust-Guided Approach to MR Image Reconstruction with Side Information	Jan 6, 2025	DiagnosticImage Reconstruction	CodeCode Available
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited Data	Aug 21, 2023	DeblurringDenoising	CodeCode Available
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction	May 25, 2023	MRI Reconstruction	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