Radiomics, the high-throughput mining of quantitative image features from standard-of-care
medical imaging that enables data to be extracted and applied within clinical-decision …

Artificial Intelligence (AI) is currently being introduced into different domains, including
medicine. Specifically in radiation oncology, machine learning models allow automation and …

Purpose This report presents the methods and results of the Thoracic Auto‐Segmentation
Challenge organized at the 2017 Annual Meeting of American Association of Physicists in …

Electronic portal imaging devices (EPIDs) have been the preferred tools for verification of
patient positioning for radiotherapy in recent decades. Since EPID images contain dose …

Purpose. Besides basic measurements as maximum standardized uptake value (SUV) max
or SUV mean derived from 18F-FDG positron emission tomography (PET) scans, more …

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

With the emergence of individualized medicine and the increasing amount and complexity
of available medical data, a growing need exists for the development of clinical decision-…

Quantitative analysis of tumour characteristics based on medical imaging is an emerging
field of research. In recent years, quantitative imaging features derived from CT, positron …

Background and purpose Contouring of organs at risk (OARs) is an important but time
consuming part of radiotherapy treatment planning. The aim of this study was to investigate …

PURPOSE: The local site of relapse in non-small cell lung cancer (NSCLC) is primarily
located in the high FDG uptake region of the primary tumour prior to treatment. A phase II PET-…