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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Dettagli Bibliografici
Pubblicato in:Quant Imaging Med Surg
Autori principali: Wang, Yunpeng, Zhou, Lingxiao, Wang, Mingming, Shao, Cheng, Shi, Lili, Yang, Shuyi, Zhang, Zhiyong, Feng, Mingxiang, Shan, Fei, Liu, Lei
Natura: Artigo
Lingua:Inglês
Pubblicazione: AME Publishing Company 2020
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Original Article
Accesso online: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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