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Background: This study aimed to compare one state-of-the-art deep learning method and four classical machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer (NSCLC) from [superscript 18]F-FDG PET/CT images.
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Contributors
- Wang, Hongkai (Author)
- Zhou, Zongwei (Author)
- Li, Yingci (Author)
- Chen, Zhonghua (Author)
- Lu, Peiou (Author)
- Wang, Wenzhi (Author)
- Liu, Wanyu (Author)
- Yu, Lijuan (Author)
- College of Health Solutions (Contributor)
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2017-01-28
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Identifier
- Digital object identifier: 10.1186/s13550-017-0260-9
- Identifier TypeInternational standard serial numberIdentifier Value2191-219X
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- The electronic version of this article is the complete one and can be found online at: https://ejnmmires.springeropen.com/articles/10.1186/s13550-017-0260-9, opens in a new window
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Wang, H., Zhou, Z., Li, Y., Chen, Z., Lu, P., Wang, W., . . . Yu, L. (2017). Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images. EJNMMI Research, 7(1). doi:10.1186/s13550-017-0260-9