Dr. Rizwan Aslam, of the University of California, San Francisco (UCSF), presented an abstract at RSNA in 2008 which showed that it was possible to screen for...
In this study, the authors evaluated the diagnostic capability, image quality, and radiation dose of abdominal ultra-low-dose CT (ULDCT) with deep learning...
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...
Pulmonary embolism (PE) is a common complication in patients with cancer. A significant number of all PE are diagnosed incidentally (incidental PE, iPE) in CT...
The aim of this study was to investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of...
Radiomics is a complex multi-step process that can be considered as part of the more complex world of Artifical Intelligence (AI). The aim of radiomics is...
This article sought to investigate the potential of generative models in the field of MRI of the spine, and did so by performing clinically relevant benchmark...
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...
This pilot study aims to investigate whether liver fibrosis can be staged by deep learning techniques based on CT images. It included CT examinations of...
In breast magnetic resonance imaging (MRI) analysis for lesion detection and classification, radiologists agree that both morphological and dynamic features...
This article attempts to predict the rupture risk in anterior communicating artery (ACOM) aneurysms by using a two-layer feed-forward artificial neural...
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...
Radiologists tend to be afraid of artificial intelligence (AI), but they should demystify it and take it for what it is, i.e. disruptive technology, according...
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...
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.