Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning–assisted nodule segmentation-Reference-Cited by-同舟云学术

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Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning–assisted nodule segmentation

Published:2020-11-21 Issue:6 Volume:31 Page:3884-3897
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Qi Lin-Lin,Wang Jian-Wei,Yang Lin,Huang Yao,Zhao Shi-Jun,Tang Wei,Jin Yu-Jing,Zhang Ze-Wei,Zhou Zhen,Yu Yi-Zhou,Wang Yi-Zhou,Wu Ning

Funder

National Key R&D Program of China

National Natural Science Foundation of China

CAMS Innovation Fund for Medical Sciences

Innovation Foundation for Doctoral Candidates of Peking Union Medical College

National Key Technology Support Program

Publisher

Springer Science and Business Media LLC

Subject

Radiology Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-020-07450-z.pdf

Reference47 articles.

1. MacMahon H, Naidich DP, Goo JM et al (2017) Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017. Radiology 284(1):228–243

2. Bueno J, Landeras L, Chung JH (2018) Updated Fleischner Society Guidelines for Managing Incidental Pulmonary Nodules: common questions and challenging scenarios. Radiographics 38(5):1337–1350

3. Travis WD, Asamura H, Bankier AA et al (2016) The IASLC Lung Cancer Staging Project: proposals for coding T categories for subsolid nodules and assessment of tumor size in part-solid tumors in the forthcoming eighth edition of the TNM classification of lung cancer. J Thorac Oncol 11(8):1204–1223

4. Aoki T (2015) Growth of pure ground-glass lung nodule detected at computed tomography. J Thorac Dis 7(9):E326–E328

5. Song YS, Park CM, Park SJ, Lee SM, Jeon YK, Goo JM (2014) Volume and mass doubling times of persistent pulmonary subsolid nodules detected in patients without known malignancy. Radiology 273(1):276–284

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