Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features
Open Access
- 25 November 2014
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Access
- Vol. 2, 1418-1426
- https://doi.org/10.1109/access.2014.2373335
Abstract
Nonsmall cell lung cancer is a prevalent disease. It is diagnosed and treated with the help of computed tomography (CT) scans. In this paper, we apply radiomics to select 3-D features from CT images of the lung toward providing prognostic information. Focusing on cases of the adenocarcinoma nonsmall cell lung cancer tumor subtype from a larger data set, we show that classifiers can be built to predict survival time. This is the first known result to make such predictions from CT scans of lung cancer. We compare classifiers and feature selection approaches. The best accuracy when predicting survival was 77.5% using a decision tree in a leave-one-out cross validation and was obtained after selecting five features per fold from 219.Funding Information
- Radiomics of Non-Small Cell Lung Cancer through the National Institutes of Health (1U01CA143062-01)
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