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 21–30 of 441 papers

Title	Date	Tasks	Status	Hype
Analysis of Deep Complex-Valued Convolutional Neural Networks for MRI Reconstruction	Apr 3, 2020	Image ReconstructionMRI Reconstruction	CodeCode Available	1
ContextMRI: Enhancing Compressed Sensing MRI through Metadata Conditioning	Jan 8, 2025	Anatomycompressed sensing	CodeCode Available	1
Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization	Mar 2, 2021	compressed sensingDeep Learning	CodeCode Available	1
Deep Low-rank plus Sparse Network for Dynamic MR Imaging	Oct 26, 2020	compressed sensingMRI Reconstruction	CodeCode Available	1
Density Compensated Unrolled Networks for Non-Cartesian MRI Reconstruction	Jan 5, 2021	MRI Reconstruction	CodeCode Available	1
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic Models	Dec 8, 2023	DenoisingImage Denoising	CodeCode Available	1
DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction with Deep T1 Prior	Jan 11, 2020	MRI Reconstruction	CodeCode Available	1
Adversarial Robust Training of Deep Learning MRI Reconstruction Models	Oct 30, 2020	Deep LearningImage Reconstruction	CodeCode Available	1
End-to-End Variational Networks for Accelerated MRI Reconstruction	Apr 14, 2020	Anatomycompressed sensing	CodeCode Available	1
A Neural-Network-Based Convex Regularizer for Inverse Problems	Nov 22, 2022	DenoisingImage Reconstruction	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