Unsupervised anomaly detection in medical images with a memory-augmented multi-level cross-attentional masked autoencoder
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 reconstruction methods, self-supervised approaches, and Imagenet pre-trained models. Reconstruction methods, which detect...
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Main Authors: | , , , , , , , , , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2023
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Online Access: | https://ink.library.smu.edu.sg/sis_research/8329 https://ink.library.smu.edu.sg/context/sis_research/article/9332/viewcontent/UnsupervisedAnomaly_av.pdf |
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Institution: | Singapore Management University |
Language: | English |