FDG-PET-derived textural features describing intra-tumor heterogeneity are increasingly
investigated as imaging biomarkers. As part of the process of quantifying heterogeneity …

Introduction “Radiomics” extracts and mines a large number of medical imaging features in a
non-invasive and cost-effective way. The underlying assumption of radiomics is that these …

Background Radiotherapy continues to be delivered without consideration of individual
tumour characteristics. To advance towards more precise treatments in radiotherapy, we …

The increasing use of biomarkers in cancer have led to the concept of personalized
medicine for patients. Personalized medicine provides better diagnosis and treatment …

Background and purpose Radiomics can quantify tumor phenotype characteristics non-
invasively by applying advanced imaging feature algorithms. In this study we assessed if pre …

Traditional radiomics involves the extraction of quantitative texture features from medical
images in an attempt to determine correlations with clinical endpoints. We hypothesize that …

Radiomics characterizes tumor phenotypes by extracting large numbers of quantitative
features from radiological images. Radiomic features have been shown to provide …

We aimed to identify optimal machine-learning methods for radiomics-based prediction of
local failure and distant failure in advanced nasopharyngeal carcinoma (NPC). We enrolled …

Introduction: In this review we describe recent developments in the field of radiomics along
with current relevant literature linking it to tumor biology. We furthermore explore the …

This paper reviews objective methods for prognostic modelling of cancer tumours located
within radiology images, a process known as radiomics. Radiomics is a novel feature …