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 71–80 of 441 papers

Title	Date	Tasks	Status	Hype	Score
Data augmentation for deep learning based accelerated MRI reconstruction with limited data	Jun 28, 2021	Data AugmentationImage Restoration	CodeCode Available	1	5
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brain	Jan 19, 2021	Data AugmentationDimensionality Reduction	CodeCode Available	1	5
Decomposition-Based Variational Network for Multi-Contrast MRI Super-Resolution and Reconstruction	Jan 1, 2023	MRI ReconstructionSuper-Resolution	CodeCode Available	1	5
Accelerated MRI with Un-trained Neural Networks	Jul 6, 2020	compressed sensingDecoder	CodeCode Available	1	5
Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization	Mar 2, 2021	compressed sensingDeep Learning	CodeCode Available	1	5
CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI?	Jun 25, 2023	MRI Reconstruction	CodeCode Available	1	5
KD-MRI: A knowledge distillation framework for image reconstruction and image restoration in MRI workflow	Apr 11, 2020	CPUGPU	CodeCode Available	1	5
Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without Noise	Nov 16, 2023	Deep LearningImage Generation	CodeCode Available	1	5
Accelerated Multi-Contrast MRI Reconstruction via Frequency and Spatial Mutual Learning	Sep 21, 2024	MRI Reconstruction	CodeCode Available	1	5
Learning Fourier-Constrained Diffusion Bridges for MRI Reconstruction	Aug 2, 2023	MRI Reconstruction	CodeCode Available	1	5

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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