CT features and quantitative analysis of subsolid nodule lung adenocarcinoma for pathological classification prediction

CT features and quantitative analysis of subsolid nodule lung adenocarcinoma for pathological classification prediction

Abstract Background The value of the CT features and quantitative analysis of lung subsolid nodules (SSNs) in the prediction of the pathological grading of lung adenocarcinoma is discussed. Methods Clinical data and CT images of 207 cases (216 lesions) with CT manifestations of an SSNs lung adenocar...

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Bibliographic Details
Main Authors: Xiaohu Li, Wei Zhang, Yongqiang Yu, Guihong Zhang, Lifen Zhou, Zongshan Wu, Bin Liu
Format: Article
Language:English
Published: BMC 2020-01-01
Series:BMC Cancer
Subjects:
Lung adenocarcinoma
Ground glass
Computed tomography
Pathology
Image features;morphological
Online Access:https://doi.org/10.1186/s12885-020-6556-6

Internet

https://doi.org/10.1186/s12885-020-6556-6

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