An annotation-free whole-slide training approach to pathological classification of lung cancer types using deep learning
Deep learning for digital pathology is hindered by the extremely high spatial resolution of whole slide images (WSIs), which requires researchers to adopt patch-based methods and laborious free-hand contouring. Here, the authors develop a whole-slide training method to classify types of lung cancers...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-02-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-21467-y |