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Found 4 papers, 1 papers with code
BiasAdv: Bias-Adversarial Augmentation for Model Debiasing
Our key idea is that an adversarial attack on a biased model that makes decisions based on spurious correlations may generate synthetic bias-conflicting samples, which can then be used as augmented training data for learning a debiased model.
Unsupervised Anomaly Detection in MR Images using Multi-Contrast Information
The feature is collaboratively used with another feature that is the low-dimensional representation of multi-contrast images.
Synthesis of Brain Tumor MR Images for Learning Data Augmentation
Deep neural networks are trained by learning data.
Attention Guided Metal Artifact Correction in MRI using Deep Neural Networks
In this paper, we observed that in a real MRI environment, two distorted images obtained with opposite polarities of readout gradient showed artifacts in a different region.
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