Disentangled Autoencoder for Cross-Stain Feature Extraction in Pathology Image Analysis
A novel deep autoencoder architecture is proposed for the analysis of histopathology images. Its purpose is to produce a disentangled latent representation in which the structure and colour information are confined to different subspaces so that stain-independent models may be learned. For this, we...
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| Hlavní autoři: | , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
MDPI AG
2020-09-01
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| Edice: | Applied Sciences |
| Témata: | |
| On-line přístup: | https://www.mdpi.com/2076-3417/10/18/6427 |
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