The natural history and treatment landscape of primary brain tumours are complicated by the
varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low …

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 …

Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have
reported results from either private institutional data or publicly available datasets. However …

Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie …

Gliomas belong to a group of central nervous system tumors, and consist of various sub-
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …

Radiomics extracts and mines large number of medical imaging features quantifying tumor
phenotypic characteristics. Highly accurate and reliable machine-learning approaches can …

Medical imaging can visualize characteristics of human cancer noninvasively. Radiomics is
an emerging field that translates these medical images into quantitative data to enable …

Background. Previous studies have shown that MR imaging features can be used to predict
survival and molecular profile of glioblastoma. However, no study of a similar type has been …

Radiomics provides a comprehensive quantification of tumor phenotypes by extracting and
mining large number of quantitative image features. To reduce the redundancy and compare …

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 …