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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Foilsithe in:Quant Imaging Med Surg
Main Authors: Wang, Yunpeng, Zhou, Lingxiao, Wang, Mingming, Shao, Cheng, Shi, Lili, Yang, Shuyi, Zhang, Zhiyong, Feng, Mingxiang, Shan, Fei, Liu, Lei
Formáid: Artigo
Teanga:Inglês
Foilsithe: AME Publishing Company 2020
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Original Article
Rochtain Ar Líne: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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