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K-space Cold Diffusion: Learning to Reconstruct Accelerated MRI without Noise
In this paper, we propose a k-space cold diffusion model that performs image degradation and restoration in k-space without the need for Gaussian noise.
MRI Field-transfer Reconstruction with Limited Data: Regularization by Neural Style Transfer
This enables RNST to reconstruct a high-quality image from a noisy low-quality image with different image styles and limited data.
Attention Hybrid Variational Net for Accelerated MRI Reconstruction
However, the drawback of these structures is that they are not fully utilizing the information from both domains (k-space and image).
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