Human-recognizable CT image features of subsolid lung nodules associated with diagnosis and classification by convolutional neural networks-Reference-Cited by-同舟云学术

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Human-recognizable CT image features of subsolid lung nodules associated with diagnosis and classification by convolutional neural networks

Published:2021-04-13 Issue:10 Volume:31 Page:7303-7315
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Jiang Beibei,Zhang Yaping,Zhang Lu,H. de Bock Geertruida,Vliegenthart Rozemarijn,Xie Xueqian^ORCID

Funder

National Natural Science Foundation of China

Ministry of Science and Technology of China

Shanghai Municipal Education Commission – Gaofeng Clinical Medicine Grant Support

Shanghai Jiao Tong University

Clinical Research Innovation Plan of Shanghai General Hospital

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-021-07901-1.pdf

Reference35 articles.

1. de Koning HJ, van der Aalst CM, de Jong PA et al (2020) Reduced lung-cancer mortality with volume CT screening in a randomized trial. N Engl J Med 382:503–513

2. Lee HW, Jin KN, Lee JK et al (2019) Long-term follow-up of ground-glass nodules after 5 years of stability. J Thorac Oncol 14:1370–1377

3. Silva M, Prokop M, Jacobs C et al (2018) Long-term active surveillance of screening detected subsolid nodules is a safe strategy to reduce overtreatment. J Thorac Oncol 13:1454–1463

4. McWilliams A, Tammemagi MC, Mayo JR et al (2013) Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med 369:910–919

5. Henschke CI, Yip R, Yankelevitz DF et al (2013) Definition of a positive test result in computed tomography screening for lung cancer: a cohort study. Ann Intern Med 158:246–252

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