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 301–310 of 441 papers

Title	Date	Tasks	Status	Hype
An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset	Oct 2, 2021	Bilevel OptimizationMeta-Learning	—Unverified	0
Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised Learning	Sep 30, 2021	compressed sensingDenoising	CodeCode Available	1
Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework	Sep 26, 2021	Image ReconstructionModel Optimization	CodeCode Available	1
End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction	Sep 23, 2021	Deep LearningImage Reconstruction	—Unverified	0
An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities	Sep 20, 2021	Image ReconstructionMRI Reconstruction	CodeCode Available	0
A review and experimental evaluation of deep learning methods for MRI reconstruction	Sep 17, 2021	compressed sensingDeep Learning	—Unverified	0
Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic results	Sep 16, 2021	compressed sensingDictionary Learning	CodeCode Available	0
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data	Sep 16, 2021	DiagnosticMRI Reconstruction	—Unverified	0
fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data	Sep 8, 2021	MRI Reconstruction	CodeCode Available	1
MRI Reconstruction Using Deep Energy-Based Model	Sep 7, 2021	Image Generationmodel	CodeCode Available	0

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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