In the ever-evolving landscape of radiology, the quest for enhanced image quality and reduced noise, particularly in obese patients, remains an enduring...
This study evaluates deep learning (DL) algorithms that are playing an increasingly important role in automatic medical image analysis. The DL algorithm used...
The aim of this study was to evaluate the performance of the LungQuant system, which is a deep learning-based software for quantitative analysis of chest CT....
The aim of this study was to present an in vivo stability analysis of radiomic features for pulmonary nodules against varying radiation dose levels. The...
This study shows that the combination of CT imaging and clinical factors pre-neoadjuvant chemotherapy (NAC) for advanced adenocarcinoma of the esophagogastric...
It is known that the reproducibility of radiomic features is influenced by myriad factors, one of which is the size of the segmented volume. We hypothesized...
The authors of this retrospective analysis looked at the role that radiomics played when applied to contrast-enhanced computed tomography (CT) in detecting...
Breast cancer continues to be the most commonly diagnosed cancer among women with over 2 million new cases per year worldwide. One important independent risk...
The authors of this retrospective study had the goal of evaluating the effectiveness of radiomics signatures in order to predict the tumor response of...
Welcome to the blog on Artificial Intelligence of the European Society of Radiology
This blog aims at bringing educational and critical perspectives on AI to readers. It should help imaging professionals to learn and keep up to date with the technologies being developed in this rapidly evolving field.