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...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Research paper
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

Internet

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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