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 281–290 of 441 papers

Title	Date	Tasks	Status
Predicting 4D Liver MRI for MR-guided Interventions	Feb 25, 2022	4D reconstructionMRI Reconstruction	—Unverified
Progressively Volumetrized Deep Generative Models for Data-Efficient Contextual Learning of MR Image Recovery	Nov 27, 2020	AnatomyMRI Reconstruction	—Unverified
Provable Preconditioned Plug-and-Play Approach for Compressed Sensing MRI Reconstruction	May 6, 2024	compressed sensingDenoising	—Unverified
Pruning Unrolled Networks (PUN) at Initialization for MRI Reconstruction Improves Generalization	Dec 24, 2024	Image ReconstructionMRI Reconstruction	—Unverified
Pyramid Convolutional RNN for MRI Image Reconstruction	Dec 2, 2019	Image ReconstructionMRI Reconstruction	—Unverified
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data	Sep 16, 2021	DiagnosticMRI Reconstruction	—Unverified
Implicit Representation of GRAPPA Kernels for Fast MRI Reconstruction	Oct 16, 2023	Image ReconstructionMRI Reconstruction	—Unverified
Real-time Dynamic MRI Reconstruction using Stacked Denoising Autoencoder	Mar 22, 2015	compressed sensingDenoising	—Unverified
Reconstructing unseen modalities and pathology with an efficient Recurrent Inference Machine	Dec 14, 2020	compressed sensingImage Reconstruction	—Unverified
Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery	Nov 27, 2017	compressed sensingDenoising	—Unverified

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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