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Combination of generative adversarial network and convolutional neural network for automatic subcentimeter pulmonary adenocarcinoma classification
BACKGROUND: The efficient and accurate diagnosis of pulmonary adenocarcinoma before surgery is of considerable significance to clinicians. Although computed tomography (CT) examinations are widely used in practice, it is still challenging and time-consuming for radiologists to distinguish between di...
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| Publicado no: | Quant Imaging Med Surg |
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| Main Authors: | , , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
AME Publishing Company
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7276356/ https://ncbi.nlm.nih.gov/pubmed/32550134 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.21037/qims-19-982 |
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