Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification
Abstract Background One challenge to train deep convolutional neural network (CNNs) models with whole slide images (WSIs) is providing the required large number of costly, manually annotated image regions. Strategies to alleviate the scarcity of annotated data include: using transfer learning, data...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BMC
2021-05-01
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| coleção: | BMC Medical Imaging |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1186/s12880-021-00609-0 |
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