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 51–60 of 441 papers

Title	Date	Tasks	Status	Hype	Score
Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization	Mar 2, 2021	compressed sensingDeep Learning	CodeCode Available	1	5
Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis	Jul 2, 2020	DenoisingImage Denoising	CodeCode Available	1	5
Deep Low-rank plus Sparse Network for Dynamic MR Imaging	Oct 26, 2020	compressed sensingMRI Reconstruction	CodeCode Available	1	5
Deep MRI Reconstruction with Radial Subsampling	Aug 17, 2021	compressed sensingDiagnostic	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
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
Fast MRI Reconstruction: How Powerful Transformers Are?	Jan 23, 2022	Generative Adversarial NetworkMRI Reconstruction	CodeCode Available	1	5
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic Models	Dec 8, 2023	DenoisingImage Denoising	CodeCode Available	1	5
DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI Reconstruction	Jan 14, 2025	DiversityMamba	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

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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