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 21–30 of 441 papers

Title	Date	Tasks	Status	Hype
MRPD: Undersampled MRI reconstruction by prompting a large latent diffusion model	Feb 16, 2024	MRI Reconstruction	CodeCode Available	1
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic Models	Dec 8, 2023	DenoisingImage Denoising	CodeCode Available	1
IMJENSE: Scan-specific Implicit Representation for Joint Coil Sensitivity and Image Estimation in Parallel MRI	Nov 21, 2023	MRI ReconstructionSensitivity	CodeCode Available	1
Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without Noise	Nov 16, 2023	Deep LearningImage Generation	CodeCode Available	1
k-t CLAIR: Self-Consistency Guided Multi-Prior Learning for Dynamic Parallel MR Image Reconstruction	Oct 17, 2023	Image ReconstructionMedical Diagnosis	CodeCode Available	1
SMRD: SURE-based Robust MRI Reconstruction with Diffusion Models	Oct 3, 2023	MRI Reconstruction	CodeCode Available	1
Fill the K-Space and Refine the Image: Prompting for Dynamic and Multi-Contrast MRI Reconstruction	Sep 25, 2023	GPUMRI Reconstruction	CodeCode Available	1
InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model	Aug 23, 2023	DecoderDenoising	CodeCode Available	1
Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms	Aug 21, 2023	Image ReconstructionMRI Reconstruction	CodeCode Available	1
Generative Priors for MRI Reconstruction Trained from Magnitude-Only Images Using Phase Augmentation	Aug 4, 2023	compressed sensingMRI Reconstruction	CodeCode Available	1

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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