Application of dual-stream 3D convolutional neural network based on (18)F-FDG PET/CT in distinguishing benign and invasive adenocarcinoma in ground-glass lung nodules

PURPOSE: This work aims to train, validate, and test a dual-stream three-dimensional convolutional neural network (3D-CNN) based on fluorine 18 ((18)F)-fluorodeoxyglucose (FDG) PET/CT to distinguish benign lesions and invasive adenocarcinoma (IAC) in ground-glass nodules (GGNs). METHODS: We retrospe...

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Detalles Bibliográficos
Autores principales: Shao, Xiaonan, Niu, Rong, Shao, Xiaoliang, Gao, Jianxiong, Shi, Yunmei, Jiang, Zhenxing, Wang, Yuetao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8561359/
https://www.ncbi.nlm.nih.gov/pubmed/34727258
http://dx.doi.org/10.1186/s40658-021-00423-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8561359/
https://www.ncbi.nlm.nih.gov/pubmed/34727258
http://dx.doi.org/10.1186/s40658-021-00423-1

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