Radiomic analysis offers a powerful tool for the extraction of clinically relevant information
from radiologic imaging. Radiomics can be used to predict patient outcome through …

After seminal papers over the period 2009–2011, the use of texture analysis of PET/CT
images for quantification of intratumour uptake heterogeneity has received increasing …

Introduction Noninvasive biomarkers that capture the total tumor burden could provide
important complementary information for precision medicine to aid clinical decision making …

Imaging with positron emission tomography (PET)/computed tomography (CT) is crucial in
the management of cancer because of its value in tumor staging, response assessment …

Background Radiomics and radiogenomics are two words that recur often in language of
radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics …

Purpose Advanced medical image analytics is increasingly used to predict clinical outcome
in patients diagnosed with gastrointestinal tumors. This review provides an overview on the …

Tumor phenotypes captured in computed tomography (CT) images can be described
qualitatively and quantitatively using radiologist-defined “semantic” and computer-derived …

Purpose To assess the value of baseline and restaging fluorine 18 (18F)
fluorodeoxyglucose (FDG) positron emission tomography (PET) radiomics in predicting …

Abstract 18 F–fluorodeoxyglucose (FDG) positron emission tomography/computed
tomography (PET/CT) is widely used for staging, evaluating treatment response, and …

Purpose To identify optimal machine learning methods for radiomics-based differentiation of
local recurrence versus inflammation from post-treatment nasopharyngeal positron emission …