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 61–70 of 441 papers

Title	Date	Tasks	Status	Hype
VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction	Nov 3, 2021	Data AugmentationMRI Reconstruction	CodeCode Available	1
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
fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data	Sep 8, 2021	MRI Reconstruction	CodeCode Available	1
High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss	Aug 27, 2021	MRI ReconstructionSSIM	CodeCode Available	1
Deep MRI Reconstruction with Radial Subsampling	Aug 17, 2021	compressed sensingDiagnostic	CodeCode Available	1
Multi-Modal MRI Reconstruction Assisted with Spatial Alignment Network	Aug 12, 2021	MRI Reconstruction	CodeCode Available	1
Uncertainty-Guided Progressive GANs for Medical Image Translation	Jun 29, 2021	DenoisingImage-to-Image Translation	CodeCode Available	1
Data augmentation for deep learning based accelerated MRI reconstruction with limited data	Jun 28, 2021	Data AugmentationImage Restoration	CodeCode Available	1
Task Transformer Network for Joint MRI Reconstruction and Super-Resolution	Jun 12, 2021	Image ReconstructionImage Super-Resolution	CodeCode Available	1

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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