Deep learning-based growth prediction for sub-solid pulmonary nodules on CT images

BACKGROUND: Estimating the growth of pulmonary sub-solid nodules (SSNs) is crucial to the successful management of them during follow-up periods. The purpose of this study is to (1) investigate the measurement sensitivity of diameter, volume, and mass of SSNs for identifying growth and (2) seek to e...

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Detalles Bibliográficos
Autores principales: Liao, Ri-qiang, Li, An-wei, Yan, Hong-hong, Lin, Jun-tao, Liu, Si-yang, Wang, Jing-wen, Fang, Jian-sheng, Liu, Hong-bo, Hou, Yong-he, Song, Chao, Yang, Hui-fang, Li, Bin, Jiang, Ben-yuan, Dong, Song, Nie, Qiang, Zhong, Wen-zhao, Wu, Yi-long, Yang, Xue-ning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9597322/
https://www.ncbi.nlm.nih.gov/pubmed/36313666
http://dx.doi.org/10.3389/fonc.2022.1002953

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9597322/
https://www.ncbi.nlm.nih.gov/pubmed/36313666
http://dx.doi.org/10.3389/fonc.2022.1002953

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