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 81–90 of 441 papers

Title	Date	Tasks	Status	Hype
MambaRecon: MRI Reconstruction with Structured State Space Models	Sep 19, 2024	MambaMRI Reconstruction	CodeCode Available	0
TC-KANRecon: High-Quality and Accelerated MRI Reconstruction via Adaptive KAN Mechanisms and Intelligent Feature Scaling	Aug 11, 2024	DenoisingImage Denoising	CodeCode Available	1
Joint PET-MRI Reconstruction with Diffusion Stochastic Differential Model	Aug 7, 2024	MRI Reconstruction	—Unverified	0
MR Optimized Reconstruction of Simultaneous Multi-Slice Imaging Using Diffusion Model	Aug 5, 2024	MRI Reconstruction	—Unverified	0
Robust Simultaneous Multislice MRI Reconstruction Using Deep Generative Priors	Jul 31, 2024	DenoisingMRI Reconstruction	CodeCode Available	0
Segmentation-guided MRI reconstruction for meaningfully diverse reconstructions	Jul 25, 2024	MRI ReconstructionSemantic Segmentation	CodeCode Available	0
GroupCDL: Interpretable Denoising and Compressed Sensing MRI via Learned Group-Sparsity and Circulant Attention	Jul 19, 2024	compressed sensingDenoising	CodeCode Available	1
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging	Jul 3, 2024	Image ReconstructionMRI Reconstruction	CodeCode Available	0
IM-MoCo: Self-supervised MRI Motion Correction using Motion-Guided Implicit Neural Representations	Jul 3, 2024	DiagnosticImage Reconstruction	CodeCode Available	1
CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI	Jun 27, 2024	Image ReconstructionMRI 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