Identifying Robust Radiomics Features for Lung Cancer by Using In-Vivo and Phantom Lung Lesions

We propose a novel framework for determining radiomics feature robustness by considering the effects of both biological and noise signals. This framework is preliminarily tested in a study predicting the epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) pa...

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書誌詳細

出版年:	Tomography
主要な著者:	Lin Lu, Shawn H. Sun, Aaron Afran, Hao Yang, Zheng Feng Lu, James So, Lawrence H. Schwartz, Binsheng Zhao
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2021-02-01
主題:	radiomics reproducibility robustness NSCLC phantom EGFR
オンライン･アクセス:	https://www.mdpi.com/2379-139X/7/1/5