In this study, the authors developed a deep feature fusion model (DFFM) in order to segment postoperative gliomas on CT images, which were guided by...
The authors of this study evaluated the impact of utilizing digital breast tomosynthesis (DBT) and/or full-field digital mammography (FFDM), and different...
In this study, the authors aimed to develop and validate a patient questionnaire on the patients’ view on the implementation of artificial intelligence...
The aim of this retrospective study was to develop non-invasive machine learning (ML) classifiers for predicting post-Glenn shunt patients with low and high...
In this study, using a semi-automatic software as a reference, the authors aimed to evaluate an artificial intelligence (AI)-based, automatic coronary artery...
In this study, the authors sought to investigate the feasibility of a deep learning-based detection (DLD) system for multiclass legions on chest radiograph....
The authors in this study aimed to evaluate the accuracy of robotic CT-guided out-of-plane needle insertion using phantom and animal experiments. A robotic...
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.
