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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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| Опубликовано в: : | Quant Imaging Med Surg |
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| Главные авторы: | , , , , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
AME Publishing Company
2020
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| Предметы: | |
| Online-ссылка: | 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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