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	Score
Adversarial Robust Training of Deep Learning MRI Reconstruction Models	Oct 30, 2020	Deep LearningImage Reconstruction	CodeCode Available	1	5
Autoregressive Image Diffusion: Generation of Image Sequence and Application in MRI	May 23, 2024	MRI Reconstruction	CodeCode Available	1	5
Fill the K-Space and Refine the Image: Prompting for Dynamic and Multi-Contrast MRI Reconstruction	Sep 25, 2023	GPUMRI Reconstruction	CodeCode Available	1	5
Generative Priors for MRI Reconstruction Trained from Magnitude-Only Images Using Phase Augmentation	Aug 4, 2023	compressed sensingMRI Reconstruction	CodeCode Available	1	5
High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss	Aug 27, 2021	MRI ReconstructionSSIM	CodeCode Available	1	5
Benchmarking MRI Reconstruction Neural Networks on Large Public Datasets	Mar 6, 2020	BenchmarkingImage Reconstruction	CodeCode Available	1	5
Adaptive Diffusion Priors for Accelerated MRI Reconstruction	Jul 12, 2022	De-aliasingMRI Reconstruction	CodeCode Available	1	5
Analysis of Deep Complex-Valued Convolutional Neural Networks for MRI Reconstruction	Apr 3, 2020	Image ReconstructionMRI Reconstruction	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
Learning Multiscale Convolutional Dictionaries for Image Reconstruction	Nov 25, 2020	Dictionary LearningImage 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