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 331–340 of 441 papers

Title	Date	Tasks	Status
Complex-valued Federated Learning with Differential Privacy and MRI Applications	Oct 7, 2021	Federated LearningMRI Reconstruction	—Unverified
Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image Enhancement	Oct 7, 2021	Image EnhancementImage-to-Image Translation	—Unverified
Accelerated First Order Methods for Variational Imaging	Oct 6, 2021	DenoisingMRI Reconstruction	CodeCode Available
An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset	Oct 2, 2021	Bilevel OptimizationMeta-Learning	—Unverified
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
An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities	Sep 20, 2021	Image ReconstructionMRI Reconstruction	CodeCode Available
A review and experimental evaluation of deep learning methods for MRI reconstruction	Sep 17, 2021	compressed sensingDeep Learning	—Unverified
Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic results	Sep 16, 2021	compressed sensingDictionary Learning	CodeCode Available
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data	Sep 16, 2021	DiagnosticMRI Reconstruction	—Unverified
MRI Reconstruction Using Deep Energy-Based Model	Sep 7, 2021	Image Generationmodel	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