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 241–250 of 441 papers

Title	Date	Tasks	Status	Hype
NPB-REC: Non-parametric Assessment of Uncertainty in Deep-learning-based MRI Reconstruction from Undersampled Data	Aug 8, 2022	Decision MakingImage Reconstruction	CodeCode Available	0
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction	Jul 18, 2022	MRI Reconstruction	CodeCode Available	0
Multi-branch Cascaded Swin Transformers with Attention to k-space Sampling Pattern for Accelerated MRI Reconstruction	Jul 18, 2022	De-aliasingMRI Reconstruction	—Unverified	0
Adaptive Diffusion Priors for Accelerated MRI Reconstruction	Jul 12, 2022	De-aliasingMRI Reconstruction	CodeCode Available	1
A deep cascade of ensemble of dual domain networks with gradient-based T1 assistance and perceptual refinement for fast MRI reconstruction	Jul 5, 2022	MRI ReconstructionSSIM	—Unverified	0
A Densely Interconnected Network for Deep Learning Accelerated MRI	Jul 5, 2022	Deep LearningMRI Reconstruction	—Unverified	0
ERNAS: An Evolutionary Neural Architecture Search for Magnetic Resonance Image Reconstructions	Jun 15, 2022	MRI ReconstructionNeural Architecture Search	—Unverified	0
A Projection-Based K-space Transformer Network for Undersampled Radial MRI Reconstruction with Limited Training Subjects	Jun 15, 2022	compressed sensingData Augmentation	—Unverified	0
Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction	Jun 15, 2022	AnatomyDe-aliasing	—Unverified	0
K-Space Transformer for Undersampled MRI Reconstruction	Jun 14, 2022	DecoderInductive Bias	CodeCode Available	1

Show:10 25 50

← PrevPage 25 of 45Next →

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