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 191–200 of 441 papers

Title	Date	Tasks	Status	Hype
Cross-Modal Vertical Federated Learning for MRI Reconstruction	Jun 5, 2023	DisentanglementFederated Learning	—Unverified	0
CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI Reconstruction	Jun 1, 2023	AnatomyContrastive Learning	CodeCode Available	0
Identification of Novel Diagnostic Neuroimaging Biomarkers for Autism Spectrum Disorder Through Convolutional Neural Network-Based Analysis of Functional, Structural, and Diffusion Tensor Imaging Data Towards Enhanced Autism Diagnosis	May 30, 2023	Brain Lesion Segmentation From MriClassification with Binary Neural Network	—Unverified	0
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction	May 25, 2023	MRI Reconstruction	CodeCode Available	0
Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz	May 12, 2023	Computed Tomography (CT)Data Augmentation	—Unverified	0
Implicit Neural Networks with Fourier-Feature Inputs for Free-breathing Cardiac MRI Reconstruction	May 11, 2023	MRI Reconstruction	CodeCode Available	1
M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research	May 10, 2023	DenoisingImage Denoising	CodeCode Available	1
Coil Sketching for computationally-efficient MR iterative reconstruction	May 10, 2023	compressed sensingComputational Efficiency	—Unverified	0
Spatial and Modal Optimal Transport for Fast Cross-Modal MRI Reconstruction	May 4, 2023	Image ReconstructionMRI Reconstruction	—Unverified	0
DD-CISENet: Dual-Domain Cross-Iteration Squeeze and Excitation Network for Accelerated MRI Reconstruction	Apr 28, 2023	DiagnosticMRI Reconstruction	—Unverified	0

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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