A deep learning based CT image analytics protocol to identify lung adenocarcinoma category and high-risk tumor area

We present a protocol which implements deep learning-based identification of the lung adenocarcinoma category with high accuracy and generalizability, and labeling of the high-risk area on Computed Tomography (CT) images. The protocol details the execution of the python project based on the dataset...

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Detalles Bibliográficos
Autores principales: Chen, Liuyin, Qi, Haoyang, Lu, Di, Zhai, Jianxue, Cai, Kaican, Wang, Long, Liang, Guoyuan, Zhang, Zijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243292/
https://www.ncbi.nlm.nih.gov/pubmed/35776652
http://dx.doi.org/10.1016/j.xpro.2022.101485

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243292/
https://www.ncbi.nlm.nih.gov/pubmed/35776652
http://dx.doi.org/10.1016/j.xpro.2022.101485

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