Automatically Predicting Lung Adenocarcinoma Invasiveness
Author:
Affiliation:
1. Sichuan University,Machine Intelligence Laboratory,School of Computer Science,Chengdu,China
2. Sichuan University,West China Hospital,Department of Thoracic Surgery,Chengdu,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9758393/9758394/09758462.pdf?arnumber=9758462
Reference31 articles.
1. Attenuation and Morphologic Characteristics Distinguishing a Ground-Glass Nodule Measuring 5–10 mm in Diameter as Invasive Lung Adenocarcinoma on Thin-Slice CT
2. Ground-Glass Nodule on Thin-Section CT: Differentiation among AdenocarcinomaIn Situ, Minimally Invasive Adenocarcinoma and Lepidic Predominant Invasive Adenocarcinoma
3. Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
4. The Correlation of the International Association for the Study of Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) Classification With Prognosis and EGFR Mutation in Lung Adenocarcinoma
5. Prognostic Significance of Adenocarcinoma In Situ, Minimally Invasive Adenocarcinoma, and Nonmucinous Lepidic Predominant Invasive Adenocarcinoma of the Lung in Patients With Stage I Disease
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