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Classification of breast cancer histopathological images using interleaved DenseNet with SENet (IDSNet)
In this study, we proposed a novel convolutional neural network (CNN) architecture for classification of benign and malignant breast cancer (BC) in histological images. To improve the delivery and use of feature information, we chose the DenseNet as the basic building block and interleaved it with t...
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| Publicado en: | PLoS One |
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| Autores principales: | , , , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Public Library of Science
2020
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7198071/ https://ncbi.nlm.nih.gov/pubmed/32365142 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0232127 |
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