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Found 2 papers, 2 papers with code
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets
In each training iteration, rather than using the fully sampled k-space for computing gradients, we use only a small k-space portion.
High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss
By adding an additional loss function on the low-dimensional feature space during training, the reconstruction frameworks from under-sampled or corrupted data can reproduce more realistic images that are closer to the original with finer textures, sharper edges, and improved overall image quality.
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