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eess.IV2022★ 1 cited
Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder
Yu Tian, Guansong Pang, Yuyuan Liu +7
Unsupervised anomaly detection (UAD) aims to find anomalous images by optimising a detector using a training set that contains only normal images. UAD approaches can be based on re…
eess.IV2022★ 1 cited
BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification
Yuanhong Chen, Fengbei Liu, Hu Wang +4
Deep learning methods have shown outstanding classification accuracy in medical imaging problems, which is largely attributed to the availability of large-scale datasets manually a…