Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale
extracted imaging information to clinical and biological endpoints. The development of …

Lung malignancies have been extensively characterized through radiomics and deep
learning. By providing a three-dimensional characterization of the lesion, models based on …

The domain of investigation of radiomics consists of large-scale radiological image analysis
and association with biological or clinical endpoints. The purpose of the present study is to …

Several reports have shown that radiomic features are affected by acquisition and
reconstruction parameters, thus hampering multicenter studies. We propose a method that …

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 …

Without doubt, artificial intelligence (AI) is the most discussed topic today in medical imaging
research, both in diagnostic and therapeutic. For diagnostic imaging alone, the number of …

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 …

Lung cancer is the second most common cancer and the leading cause of cancer-related
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …

Routine follow-up visits and radiographic imaging are required for outcome evaluation and
tumor recurrence monitoring. Yet more personalized surveillance is required in order to …

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