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
A Deep Learning Approach for Parallel Imaging and Compressed Sensing MRI Reconstruction	Sep 19, 2022	compressed sensingDe-aliasing	—Unverified
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
Image Restoration by Combined Order Regularization with Optimal Spatial Adaptation	Mar 7, 2019	Image RestorationMRI Reconstruction	—Unverified
Implicit Neural Representation-Based MRI Reconstruction Method with Sensitivity Map Constraints	Jun 6, 2025	DiagnosticMRI Reconstruction	—Unverified
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning	May 10, 2021	MRI ReconstructionSelf-Supervised Learning	—Unverified
INFusion: Diffusion Regularized Implicit Neural Representations for 2D and 3D accelerated MRI reconstruction	Jun 19, 2024	Image ReconstructionMRI Reconstruction	—Unverified
Invertible Sharpening Network for MRI Reconstruction Enhancement	Jun 6, 2022	DiagnosticMRI Reconstruction	—Unverified
IWNeXt: an image-wavelet domain ConvNeXt-based network for self-supervised multi-contrast MRI reconstruction	Apr 3, 2024	MRI ReconstructionSelf-Supervised Learning	—Unverified
Joint Calibrationless Reconstruction and Segmentation of Parallel MRI	May 19, 2021	Image ReconstructionMRI Reconstruction	—Unverified
Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network	May 6, 2018	compressed sensingDecoder	—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