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Found 3 papers, 2 papers with code
Adversarial Robust Training of Deep Learning MRI Reconstruction Models
These results are encouraging, and highlight the necessity for attention to this problem by the image reconstruction community, as a milestone for the introduction of DL reconstruction in clinical practice.
Addressing The False Negative Problem of MRI Reconstruction Networks by Adversarial Attacks and Robust Training
Deep learning models have been shown to be successful in accelerating MRI reconstruction, over traditional methods.
Adversarial Policy Gradient for Deep Learning Image Augmentation
The use of semantic segmentation for masking and cropping input images has proven to be a significant aid in medical imaging classification tasks by decreasing the noise and variance of the training dataset.
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