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Found 3 papers, 2 papers with code
Generalizing Supervised Deep Learning MRI Reconstruction to Multiple and Unseen Contrasts using Meta-Learning Hypernetworks
The hypernetworks and the reconstruction network in the GBML setting provide discriminative mode-specific features and low-level image features, respectively.
Generalizable Deep Learning Method for Suppressing Unseen and Multiple MRI Artifacts Using Meta-learning
Conventional deep learning methods deal with removing a specific type of artifact, leading to separately trained models for each artifact type that lack the shared knowledge generalizable across artifacts.
A Study of Representational Properties of Unsupervised Anomaly Detection in Brain MRI
Anomaly detection in MRI is of high clinical value in imaging and diagnosis.
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