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Found 2 papers, 1 papers with code
SRNR: Training neural networks for Super-Resolution MRI using Noisy high-resolution Reference data
Neural network (NN) based approaches for super-resolution MRI typically require high-SNR high-resolution reference data acquired in many subjects, which is time consuming and a barrier to feasible and accessible implementation.
Improving accuracy and uncertainty quantification of deep learning based quantitative MRI using Monte Carlo dropout
Dropout is conventionally used during the training phase as regularization method and for quantifying uncertainty in deep learning.
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