Reproducibility and Prognosis of Quantitative Features Extracted from CT Images.

ABSTRACT: We study the reproducibility of quantitative imaging features that are used to describe tumor shape, size, and texture from computed tomography (CT) scans of non-small cell lung cancer (NSCLC). CT images are dependent on various scanning factors. We focus on characterizing image features that are reproducible in the presence of variations due to patient factors and segmentation methods. Thirty-two NSCLC nonenhanced lung CT scans were obtained from the Reference Image Database to Evaluate Response data set. The tumors were segmented using both manual (radiologist expert) and ensemble (software-automated) methods. A set of features (219 three-dimensional and 110 two-dimensional) was computed, and quantitative image features were statistically filtered to identify a subset of reproducible and

SUBMITTER: Balagurunathan Y 

PROVIDER: S-EPMC3998690 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature