A new study sees the development of a fully automatic framework for the diagnosis of the cause of left ventricular hypertrophy (LVH) via cardiac cine images....
The authors of this study developed a CT-based artificial intelligence model with the ability to differentiate between benign and malignant ovarian tumors,...
Although structured reporting (SR) is recommended in the field of radiology compared to free-text reporting (FTR), the use of SR still experiences obstacles...
This study seeks to determine if artificial intelligence (AI)-based software can improve radiologists’ performance when detecting clinically significant...
The COVID-19 pandemic not only made an impact on the discipline of radiology as a whole but also on how we use specific tools in its detection. This was...
As computed tomography (CT) sees an increase in utilization, inappropriate imaging has been seen as a significant concern; however, manual justification...
The authors of this study investigated whether radiomics based on T2-weighted MRI was able to discriminate between benign and borderline epithelial ovarian...
This study shows that the combination of CT imaging and clinical factors pre-neoadjuvant chemotherapy (NAC) for advanced adenocarcinoma of the esophagogastric...
This study explores the importance of quality assurance when deploying an automatic segmentation model. The authors of this study built a deep-learning model...
The aim of this study was to provide an updated systematic review of radiomics in osteosarcoma, utilizing various databases such as PubMed, Embase, China...
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.