Development of a deep learning‐based method to diagnose pulmonary ground‐glass nodules by sequential computed tomography imaging

BACKGROUND: Early identification of the malignant propensity of pulmonary ground‐glass nodules (GGNs) can relieve the pressure from tracking lesions and personalized treatment adaptation. The purpose of this study was to develop a deep learning‐based method using sequential computed tomography (CT)...

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Detalles Bibliográficos
Autores principales: Qiu, Zhixin, Wu, Qingxia, Wang, Shuo, Chen, Zhixia, Lin, Feng, Zhou, Yuyan, Jin, Jing, Xian, Jinghong, Tian, Jie, Li, Weimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons Australia, Ltd 2022
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841714/
https://www.ncbi.nlm.nih.gov/pubmed/34994091
http://dx.doi.org/10.1111/1759-7714.14305

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841714/
https://www.ncbi.nlm.nih.gov/pubmed/34994091
http://dx.doi.org/10.1111/1759-7714.14305

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