In this article, we extracted “hand-crafted” radiomic features from dual-energy CT (DECT) virtual monochromatic images (VMIs) reconstructed at different...
Radiomic workflows include various challenging steps. One of the most demanding steps in radiomics is the segmentation process. Particularly for the renal...
Over the last years, medicine has been moving further towards providing a more tailored, patient-centric approach by taking into account as much information...
In this study, the authors investigated how feasible it was to use 3D convolutional neural networks (CNN) to detect ischemic stroke from computed tomography...
These days, selling a medical product or software solution without bringing up ‘artificial intelligence’ seems to be an almost impossible task. Hence, a...
The aim of this narrative review is to take a broader look at the application of Artificial Intelligence (AI), primarily in medical imaging. The authors...
The field of medical imaging has witnessed a revolution thanks to the digital transformation, innovation and availability of advanced clinical applications....
Numerous domains, including radiology, have shown interest in convolutional neural network (CNN) – a class of artificial neural networks that has become...
Imagine you wanted to teach a baby to differentiate a ball from a dog. How would you do that? Intuitively it would make sense to repeatedly point at them...
The topic of artificial intelligence (AI) has become one of the main points of discussion in the field of radiology and medicine. Through discussions on...
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.