Statistical Analysis on Impact of Image Preprocessing of CT Texture Patterns and Its CT Radiomic Feature Stability: A Phantom Study (original) (raw)

Asian Pacific Journal of Cancer Prevention

Recent advances in quantitative imaging (radiomics) traits are utilized to determine how well a tumor is benign or malignant (Bayanati et al., 2015). Radiomics is also renowned for characterizing tumor heterogeneity and phenotypes using high throughput quantified features derived from clinical standards of image-based biomarkers related to pathologic, genomic, proteomic, and clinical data (Lambin P et al., 2012). It is used as a predictive tool for clinical decision-making in detecting Non-small cell lung cancer (NSCLC) tumor genetic mutations (Weiss GJ et al., 2014). The response evaluates an early potential biomarker for therapy (Bertelsen et al., 2011; Bernchou