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 381–390 of 441 papers

Title	Date	Tasks	Status
Co-VeGAN: Complex-Valued Generative Adversarial Network for Compressive Sensing MR Image Reconstruction	Feb 24, 2020	Compressive SensingGenerative Adversarial Network	—Unverified
Learning to Predict Error for MRI Reconstruction	Feb 13, 2020	Medical DiagnosisMRI Reconstruction	—Unverified
Addressing The False Negative Problem of MRI Reconstruction Networks by Adversarial Attacks and Robust Training	Jan 25, 2020	DiagnosticMRI Reconstruction	—Unverified
Breaking Speed Limits with Simultaneous Ultra-Fast MRI Reconstruction and Tissue Segmentation	Jan 25, 2020	MRI ReconstructionSegmentation	—Unverified
Spherical function regularization for parallel MRI reconstruction	Jan 25, 2020	MRI Reconstruction	—Unverified
ODE-based Deep Network for MRI Reconstruction	Dec 27, 2019	Image ReconstructionMRI Reconstruction	—Unverified
An Unsupervised Deep Learning Method for Multi-coil Cine MRI	Dec 20, 2019	Deep LearningMRI Reconstruction	CodeCode Available
Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms	Dec 16, 2019	MRI ReconstructionRolling Shutter Correction	—Unverified
Self-Supervised Learning of Physics-Guided Reconstruction Neural Networks without Fully-Sampled Reference Data	Dec 16, 2019	compressed sensingMRI Reconstruction	CodeCode Available
Pyramid Convolutional RNN for MRI Image Reconstruction	Dec 2, 2019	Image ReconstructionMRI 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