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 151–160 of 441 papers

Title	Date	Tasks	Status
Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction	Oct 25, 2018	compressed sensingImage Reconstruction	—Unverified
A deep cascade of ensemble of dual domain networks with gradient-based T1 assistance and perceptual refinement for fast MRI reconstruction	Jul 5, 2022	MRI ReconstructionSSIM	—Unverified
Exploring Siamese Networks in Self-Supervised Fast MRI Reconstruction	Jan 18, 2025	MRI ReconstructionSelf-Supervised Learning	—Unverified
Compressed Sensing MRI via a Multi-scale Dilated Residual Convolution Network	Jun 11, 2019	compressed sensingMRI Reconstruction	—Unverified
A New k-Space Model for Non-Cartesian Fourier Imaging	May 8, 2025	MRI Reconstruction	—Unverified
Self-Supervised Adversarial Diffusion Models for Fast MRI Reconstruction	Jun 21, 2024	compressed sensingMRI Reconstruction	—Unverified
Compressed Sensing MRI Reconstruction Regularized by VAEs with Structured Image Covariance	Oct 26, 2022	compressed sensingMRI Reconstruction	—Unverified
Addressing The False Negative Problem of MRI Reconstruction Networks by Adversarial Attacks and Robust Training	Jan 25, 2020	DiagnosticMRI Reconstruction	—Unverified
eRAKI: Fast Robust Artificial neural networks for K-space Interpolation (RAKI) with Coil Combination and Joint Reconstruction	Jul 7, 2021	MRI Reconstruction	—Unverified
Complex-valued Federated Learning with Differential Privacy and MRI Applications	Oct 7, 2021	Federated LearningMRI Reconstruction	—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