AI Blog

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.

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Latest posts

Artificial intelligence in publications: an interview with Professor Yves Menu

Throughout this series, we will get an inside look at the topic of artificial intelligence (AI) in relation to radiological journals over three brief interviews with the Editors-in-Chief of the European Society of Radiology’s three flagship journals: European Radiology (Professor Yves Menu), European Radiology Experimental (Professor Francesco Sardanelli), and Insights into Imaging (Professor Luis Martí-Bonmatí). This week, we begin with

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Why radiomics research does not translate to clinical practice: evaluation of literature using RQS and TRIPOD

Over the last few years, the number of studies published using quantitative imaging biomarkers to classify or predict pathologies has steadily increased. As of today, a quick PubMed search for radiomics, imaging biomarkers or radiogenomics reveals well over 4,000 articles. However, somewhat surprisingly, given this amount of published research, outside of academic literature there is no widespread clinical application of

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The Not-So-Narrow Artificial Narrow Intelligence

Artificial Intelligence (AI) and healthcare are converging in ways never imagined and the benefits to the healthcare system are only now being realized in full. When we think of AI in societal terms, the broad spectrum of artificial superintelligence is usually what comes to mind. Let’s get a better idea of the trajectory so we can understand the potential impacts

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Radiation dose in pregnancy

Due to the high radiosensitivity of the fetus and embryo, diagnostic imaging procedures for pregnant patients raise health concerns. Therefore, the authors of this work set out to develop a methodology for automated construction of patient-specific computational phantoms based on actual patient CT images with the aim of achieving accurate estimate of conceptus dose. Key points The conceptus dose during

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AI power is real but muzzled by lack of data sharing and standardization

AI adds a new dimension to brain and abdominal imaging in a number of clinical scenarios, but lack of data sharing as well as reproducibility and standardization issues must be addressed, top European radiologists explained during the ESR AI Premium event. Detecting the invisible and the visible In the brain, AI can help to detect things that are invisible to

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Deep learning to differentiate parkinsonian disorders separately using single midsagittal MR imaging

In an attempt to determine whether deep learning with the convolutional neural networks (CNN) can be used for identifying parkinsonian disorder on MRI, the authors of this study trained the CNN to distinguish each parkinsonian disorder and then assessed the CNN’s performance. The levels of accuracy achieved confirmed that deep learning with CNN can discriminate parkinsonian disorders with high accuracy.

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AI-assisted education for rads: challenges and promises

The first meeting of the European Society of Radiology (ESR) dedicated to Artificial Intelligence (AI) gathered a large panel of delegates from different counties and backgrounds, yet they all had one thing in common: during their education, they all used old books and didactical procedures, which, in most cases, are out-dated. AI could help boost education in many fields, including

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Are semi-automated software programs designed for adults accurate for the identification of vertebral fractures in children?

The goal of this study was to test if using AVERT™ (a 33-point semi-automated program developed for VF diagnosis in adults) is better for morphometric vertebral fracture (VF) diagnosis in children than using SpineAnalyzer™, a 6-point program which has previously been shown to be of insufficient accuracy. The authors were able to conclude that, although VERT™ has slightly higher accuracy

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Zooming in on AI-Based Image Interpretation

While the use of artificial intelligence (AI) in radiology eases workflows, it may also lead to a better and more precise understanding of disease. Predicting the course of cancer from imaging data could become a part of the clinical routine in the next few years. Many experts believe that the increasing use of AI in radiology will fundamentally change the

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Machine learning classifiers vs. Experienced radiologists: Predicting Gleason pattern 4 prostate cancer

The authors of this study recognized the potential of multiparametric positron emission tomography/magnetic resonance imaging (mpPET/MRI) for detecting and classifying breast lesions. To better understand computer-aided segmentation and diagnosis (CAD) features, the authors introduced a data-driven machine learning approach for a CAD system that enables the assessment of the relevance of mpPET/MRI features on segmentation and classification accuracy. Key points:

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Become A Member Today!

You will have access to a wide range of benefits that can help you advance your career and stay up-to-date with the latest developments in the field of radiology. These benefits include access to educational resources, networking opportunities with other professionals in the field, opportunities to participate in research projects and clinical trials, and access to the latest technologies and techniques. 

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for radiologists, radiology residents, professionals of allied sciences (including radiographers/radiological technologists, nuclear medicine physicians, medical physicists, and data scientists) & professionals of allied sciences in training residing within the boundaries of Europe

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  • Reduced registration fees for ECR 1
  • Free electronic access to the journal European Radiology
  • Content e-mails for all 3 ESR journals 4
  • Updates on offers & events through our newsletters
  • Exclusive access to the ESR feed in Juisci

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Reduced registration fees for ECR 2024:
Provided that ESR 2023 membership is activated and approved by August 31, 2023.

Reduced registration fees for ECR 2025:
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Not all activities included
Examination based on the ESR European Training Curriculum (radiologists or radiology residents).
European Radiology, Insights into Imaging, European Radiology Experimental.