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 141–150 of 441 papers

Title	Date	Tasks	Status
eRAKI: Fast Robust Artificial neural networks for K-space Interpolation (RAKI) with Coil Combination and Joint Reconstruction	Jul 7, 2021	MRI Reconstruction	—Unverified
ERNAS: An Evolutionary Neural Architecture Search for Magnetic Resonance Image Reconstructions	Jun 15, 2022	MRI ReconstructionNeural Architecture Search	—Unverified
4D MRI: Robust sorting of free breathing MRI slices for use in interventional settings	Oct 4, 2019	MRI Reconstruction	—Unverified
Contrastive Learning for Local and Global Learning MRI Reconstruction	Nov 30, 2021	Contrastive LearningMRI Reconstruction	—Unverified
Encoding Enhanced Complex CNN for Accurate and Highly Accelerated MRI	Jun 21, 2023	Image ReconstructionMRI Reconstruction	—Unverified
Continuous K-space Recovery Network with Image Guidance for Fast MRI Reconstruction	Nov 18, 2024	DecoderMRI Reconstruction	—Unverified
A Deep Error Correction Network for Compressed Sensing MRI	Mar 23, 2018	compressed sensingDiagnostic	—Unverified
Encoding Semantic Priors into the Weights of Implicit Neural Representation	Jun 6, 2024	CT ReconstructionMRI Reconstruction	—Unverified
An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset	Oct 2, 2021	Bilevel OptimizationMeta-Learning	—Unverified
Conditional WGANs with Adaptive Gradient Balancing for Sparse MRI Reconstruction	May 2, 2019	Generative Adversarial NetworkMRI 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