Radiomics is a quantitative approach to medical imaging, which aims at enhancing the
existing data available to clinicians by means of advanced mathematical analysis. Through …

Radiomics is an emerging translational field of research aiming to extract mineable high-
dimensional data from clinical images. The radiomic process can be divided into distinct …

The impact of PET image acquisition and reconstruction parameters on SUV measurements
or radiomic feature values is widely documented. This scanner effect is detrimental to the …

Textural and shape analysis is gaining considerable interest in medical imaging, particularly
to identify parameters characterizing tumor heterogeneity and to feed radiomic models …

Over the last decade there has been an extensive evolution in the Artificial Intelligence (AI)
field. Modern radiation oncology is based on the exploitation of advanced computational …

Radiomics in nuclear medicine is rapidly expanding. Reproducibility of radiomics studies in
multicentre settings is an important criterion for clinical translation. We therefore performed a …

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

Purpose The aim of this systematic review was to analyse literature on artificial intelligence
(AI) and radiomics, including all medical imaging modalities, for oncological and non …

Objective Test a practical realignment approach to compensate the technical variability of
MR radiomic features. Methods T1 phantom images acquired on 2 scanners, FLAIR and …

An important need exists for strategies to perform rigorous objective clinical-task-based
evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need …