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

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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Bibliographic Details
Main Authors: Lin Lu, Shawn H. Sun, Aaron Afran, Hao Yang, Zheng Feng Lu, James So, Lawrence H. Schwartz, Binsheng Zhao
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Tomography
Subjects:
radiomics
reproducibility
robustness
NSCLC
phantom
EGFR
Online Access:https://www.mdpi.com/2379-139X/7/1/5

Internet

https://www.mdpi.com/2379-139X/7/1/5

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