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	Score
ATOMMIC: An Advanced Toolbox for Multitask Medical Imaging Consistency to facilitate Artificial Intelligence applications from acquisition to analysis in Magnetic Resonance Imaging	Apr 30, 2024	BenchmarkingImage Reconstruction	CodeCode Available	1	5
Assessment of Data Consistency through Cascades of Independently Recurrent Inference Machines for fast and robust accelerated MRI reconstruction	Nov 30, 2021	DenoisingImage 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
CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI?	Jun 25, 2023	MRI Reconstruction	CodeCode Available	1	5
DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI Reconstruction	Jan 14, 2025	DiversityMamba	CodeCode Available	1	5
Benchmarking MRI Reconstruction Neural Networks on Large Public Datasets	Mar 6, 2020	BenchmarkingImage Reconstruction	CodeCode Available	1	5
Dynamic Cardiac MRI Reconstruction Using Combined Tensor Nuclear Norm and Casorati Matrix Nuclear Norm Regularizations	Jun 2, 2022	Computational EfficiencyMRI Reconstruction	CodeCode Available	1	5
Adversarial Robust Training of Deep Learning MRI Reconstruction Models	Oct 30, 2020	Deep LearningImage Reconstruction	CodeCode Available	1	5
Accelerated MRI with Un-trained Neural Networks	Jul 6, 2020	compressed sensingDecoder	CodeCode Available	1	5
A Neural-Network-Based Convex Regularizer for Inverse Problems	Nov 22, 2022	DenoisingImage 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