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Computer-aided diagnosis of laryngeal cancer via deep learning based on laryngoscopic images
OBJECTIVE: To develop a deep convolutional neural network (DCNN) that can automatically detect laryngeal cancer (LCA) in laryngoscopic images. METHODS: A DCNN-based diagnostic system was constructed and trained using 13,721 laryngoscopic images of LCA, precancerous laryngeal lesions (PRELCA), benign...
Autores principales: | Xiong, Hao, Lin, Peiliang, Yu, Jin-Gang, Ye, Jin, Xiao, Lichao, Tao, Yuan, Jiang, Zebin, Lin, Wei, Liu, Mingyue, Xu, Jingjing, Hu, Wenjie, Lu, Yuewen, Liu, Huaifeng, Li, Yuanqing, Zheng, Yiqing, Yang, Haidi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838439/ https://www.ncbi.nlm.nih.gov/pubmed/31594753 http://dx.doi.org/10.1016/j.ebiom.2019.08.075 |
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