SOTAVerified

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

Showing 211220 of 441 papers

TitleStatusHype
How Should We Evaluate Uncertainty in Accelerated MRI Reconstruction?0
Holistic Multi-Slice Framework for Dynamic Simultaneous Multi-Slice MRI Reconstruction0
Data augmentation for deep learning based accelerated MRI reconstruction0
A scan-specific unsupervised method for parallel MRI reconstruction via implicit neural representation0
A Densely Interconnected Network for Deep Learning Accelerated MRI0
High-Resolution Pelvic MRI Reconstruction Using a Generative Adversarial Network with Attention and Cyclic Loss0
Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers0
Data and Physics driven Deep Learning Models for Fast MRI Reconstruction: Fundamentals and Methodologies0
Hybrid Learning: A Novel Combination of Self-Supervised and Supervised Learning for MRI Reconstruction without High-Quality Training Reference0
A Scale Invariant Approach for Sparse Signal Recovery0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HUMUS-Net (train+val data)SSIM0.89Unverified
2HUMUS-Net (train only)SSIM0.89Unverified
3End-to-end variational networkSSIM0.89Unverified
4XPDNetSSIM0.89Unverified
#ModelMetricClaimedVerifiedStatus
1PromptMRSSIM0.9Unverified
2HUMUS-Net-LSSIM0.9Unverified
3HUMUS-NetSSIM0.89Unverified
4E2E-VarNet (train+val)SSIM0.89Unverified
#ModelMetricClaimedVerifiedStatus
1End-to-end variational networkSSIM0.96Unverified
2XPDNetSSIM0.96Unverified
#ModelMetricClaimedVerifiedStatus
1End-to-end variational networkSSIM0.94Unverified
2XPDNetSSIM0.94Unverified
#ModelMetricClaimedVerifiedStatus
1End-to-end variational networkSSIM0.93Unverified
2XPDNetSSIM0.93Unverified
#ModelMetricClaimedVerifiedStatus
1Residual U-NETDSSIM0Unverified