On this page, you will find interesting information about the ESR, including facts & figures, details about the executive council, our guiding principles, and much more. Discover everything there is to know about the ESR.

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Part of our mission statement is “Advancing you,” and on this page, you’ll find all of our educational programmes, courses, eBooks, partner links, and downloads, etc., designed to enhance your knowledge and advance your career.

Visit this page for more information about our journals: European Radiology, Insights into Imaging, and European Radiology Experimental, as well as information about Eurorad. Additionally, if you’re interested in publishing your own work, you can find details here.

On this page, patients can find crucial information for their journey towards health, as the European Society of Radiology is at the forefront of advancing patient care and ensuring that individuals receive the assistance they need.

Discover information about our research endeavors and how EIBIR is shaping the future of radiology. Additionally, you’ll find news about research grants, statistics, and details about EIBALL and our Biomarker Inventory.

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Learn more about how the ESR is advancing quality and safety standards in radiology, and access all the information on ESR iGuide, Eurosafe Imaging, our clinical audit tool, as well as ESR-led projects and papers.

Here, you can find information about the ESR’s communal approach to radiology, its relations with EU institutions, international organisations, and other stakeholders, as well as European projects and alliances.

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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.

Most used hashtags:

machine learningdeep learningmriradiomicsx-ray computed tomographyai newsCOVID-19mammographyinterviewbreast cancerdiagnostic imagingneural networkstomographyMDCTworkflowradiography

Latest posts

Test-retest reproducibility of a deep learning–based automatic detection algorithm for the chest radiograph

European Radiology April 2020

The authors of this retrospective study performed test-retest reproducibility analyses for a deep learning-based automatic detection algorithm (DLAD) using two stationary chest radiographs with short-term intervals, in order to analyze influential factors on test-retest variations. The test, which included patients with pulmonary nodules resected in 2017, showed that DLAD was robust to the test-retest variation. Key points The deep learning–based

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Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound

European Radiology April 2020

The aim of this study was to establish and validate an artificial intelligence-based radiomics strategy in order to predict personalized responses to hepatocellular carcinoma (HCC) to first transarterial chemoembolization (TACE) by analyzing contrast-enhanced ultrasound (CEUS) cines quantitatively. This was done using 130 HCC patients, showing that a deep learning-based radiomics method can effectively utilize CEUS, resulting in accurate and personalized

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Deep learning workflow in radiology: how to get started

An Tang March 2020

In the past decade, deep learning architectures, which essentially consist of neural networks with numerous layers, have emerged as a dominant class of machine learning algorithms. Owing to the availability of larger datasets in radiology and access to high-performance graphical processing units, deep learning has provided state-of-the-art performance for various computer vision tasks such as lesion detection, segmentation, classification, monitoring,

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Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis

Philipp Kickingereder March 2020

Multiple automated methods for segmentation of multiple sclerosis (MS) lesions have been developed over the past years, and the use of artificial neural networks (ANN) has recently generated many outstanding results in the public segmentation challenges. As we all know from our work as radiologists, the routine clinical practice is always conducted with an economical balance between optimal scan times

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Looking outside the box: AI in the fight against COVID-19, how our society is being transformed by tech, and sensors analyzing your football skills

ESR March 2020

This week in artificial intelligence (AI) news, we take a look at AI and other tech being used to fight novel coronavirus (COVID-19), how AI and technology are impacting our society, and the implications for wearable tech. As the novel coronavirus (COVID-19) spreads throughout the world, individuals from various backgrounds and disciplines, such as healthcare and tech, are coming together

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Dual-energy CT–based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer

European Radiology March 2020

In this study, the authors aimed to build a dual-energy CT (DECT)-based deep learning radiomics nomogram that could be used for lymph node metastasis prediction in gastric cancer. Ultimately, the DECT-based deep learning radiomics nomogram operated well in predicting lymph node metastasis in gastric cancer. Key points This study investigated the value of deep learning dual-energy CT–based radiomics in predicting

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AI in radiology: What patients really want – the best possible diagnosis with the highest possible precision

Melisande Rouger March 2020

Communication between radiologists and patients will take centre stage at ECR, which will be held in July of this year, and many think AI is an opportunity to improve this relationship. Patient experience with algorithms used in radiology has been positive, but issues regarding patient data privacy must still be made clear. Improving reporting There is a lot of potential

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Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas?

European Radiology March 2020

In this study, the authors aimed to improve the prediction of patients’ prognosis of myxoid/round cell liposarcomas (MRC-LPS) using a radiomics approach. 35 patients with MRC-LPS were included in this retrospective study. They found that the best prediction of metastatic relapse-free survival for MRC-LPS was achieved by combining the radiomics score to relevant radiological features. Key points Fourteen radiomics features

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Marginal radiomics features as imaging biomarkers for pathological invasion in lung adenocarcinoma

European Radiology March 2020

This study identified 236 patients from two cohorts who underwent surgery for ground-glass nodules (GGNs). The novel marginal features described, when combined with a radiomics model, could help to differentiate invasive adenocarcinoma (IA) from adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) on preoperative CT scans. Key points Our novel marginal features could improve the existing radiomics model to

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Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers and Readers

Daniel Pinto dos Santos February 2020

In recent years, we have seen a sharp increase in publications concerning machine learning and deep learning in radiology. Consequently, some journals report that around a quarter of all their publications in 2018 related to these topics, one way or another. Of course, with so much research around, it is important to be able to assess concerns of scientific quality.

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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. 

Check out our different membership options.

If you don’t find a fitting membership send us an email here.

①

Membership

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

  • Reduced registration fees for ECR 1
  • Reduced fees for the European School of Radiology (ESOR) 2
  • Option to participate in the European Diploma. 3
  • Free electronic access to the journal European Radiology 4
  • Content e-mails for all ESR journals
  • Updates on offers & events through our newsletters
  • Exclusive access to the ESR feed in Juisci

€ 11 /year

Yes! That is less than €1 per month.
②

Free membership

for radiologists, radiology residents or professionals of allied sciences engaged in practice, teaching or research residing outside Europe as well as individual qualified professionals with an interest in radiology and medical imaging who do not fulfil individual or all requirements for any other ESR membership category & former full members who have retired from all clinical practice
  • Reduced registration fees for ECR 1
  • Option to participate in the European Diploma. 3
  • 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

€ 0

The best things in life are free.
③

ESR Friends

For students, company representatives or hospital managers etc.

  • Content e-mails for all 3 ESR journals 4
  • Updates on offers & events through our newsletters

€ 0

Friendship doesn’t cost a thing.
Apply now

The membership type best fitting for you will be selected automatically during the application process.

Footnotes:

01

Reduced registration fees for ECR 2025:
Provided that ESR 2024 membership is activated and approved by August 31, 2024.

02
Not all activities included
03
Examination based on the ESR European Training Curriculum (radiologists or radiology residents).
04
European Radiology, Insights into Imaging, European Radiology Experimental.