The missing modality issue is critical but non-trivial to be solved by
m...
State-of-the-art (SOTA) deep learning mammogram classifiers, trained wit...
When analysing screening mammograms, radiologists can naturally process
...
Multi-modal learning focuses on training models by equally combining mul...
3D medical image segmentation methods have been successful, but their
de...
Deep learning methods have shown outstanding classification accuracy in
...
Effective semi-supervised learning (SSL) in medical im-age analysis (MIA...
Consistency learning using input image, feature, or network perturbation...
Unsupervised anomaly detection (UAD) learns one-class classifiers exclus...
Current unsupervised anomaly detection and localisation systems are comm...
In this paper, we address the problem of weakly-supervised video anomaly...