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
Adversarial Robust Training of Deep Learning MRI Reconstruction Models	Oct 30, 2020	Deep LearningImage Reconstruction	CodeCode Available	1
Autoregressive Image Diffusion: Generation of Image Sequence and Application in MRI	May 23, 2024	MRI Reconstruction	CodeCode Available	1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brain	Jan 19, 2021	Data AugmentationDimensionality Reduction	CodeCode Available	1
DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI Reconstruction	Jan 14, 2025	DiversityMamba	CodeCode Available	1
Data augmentation for deep learning based accelerated MRI reconstruction with limited data	Jun 28, 2021	Data AugmentationImage Restoration	CodeCode Available	1
Benchmarking MRI Reconstruction Neural Networks on Large Public Datasets	Mar 6, 2020	BenchmarkingImage Reconstruction	CodeCode Available	1
Adaptive Diffusion Priors for Accelerated MRI Reconstruction	Jul 12, 2022	De-aliasingMRI Reconstruction	CodeCode Available	1
Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization	Mar 2, 2021	compressed sensingDeep Learning	CodeCode Available	1
Deep MRI Reconstruction with Radial Subsampling	Aug 17, 2021	compressed sensingDiagnostic	CodeCode Available	1
Fast MRI Reconstruction: How Powerful Transformers Are?	Jan 23, 2022	Generative Adversarial NetworkMRI 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