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.
You’re interested in learning more about an ESR membership? Well, you’ve come to the right page. Here, you can discover everything about our memberships, including the benefits and prices. We are sure that you’ll find the perfect option for you.
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.
This is the page for all things ECR and our other events. Learn everything about how to register, submit abstracts, attend in person, become an exhibitor, and much more. There is no congress like ECR. Start your journey here.
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.
This is where you log into the MyUserArea, where you can find all the information regarding your membership, renew it, and book additional packages or register for ECR.
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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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
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.
Convolutional neural networks (CNN) have demonstrated the potential to become effective and accurate decision support tools for radiologists. A major barrier to clinical translation, however, is that the majority of such algorithms currently function like a “black box”. After training a CNN with a large set of input and output data, its internal layers are automatically adjusted to mathematically “map”
Numerous domains, including radiology, have shown interest in convolutional neural network (CNN) – a class of artificial neural networks that has become dominant in various computer vision tasks. It is designed to automatically and adaptively learn spatial hierarchies of features through backpropagation by using multiple building blocks, such as convolution layers, pooling layers, and fully connected layers. This review article
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
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.
Convolutional neural networks (CNN) have demonstrated the potential to become effective and accurate decision support tools for radiologists. A major barrier to clinical translation, however, is that the majority of such algorithms currently function like a “black box”. After training a CNN with a large set of input and output data, its internal layers are automatically adjusted to mathematically “map”
Numerous domains, including radiology, have shown interest in convolutional neural network (CNN) – a class of artificial neural networks that has become dominant in various computer vision tasks. It is designed to automatically and adaptively learn spatial hierarchies of features through backpropagation by using multiple building blocks, such as convolution layers, pooling layers, and fully connected layers. This review article
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.
If you don’t find a fitting membership send us an email here.
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
€ 11 /year
€ 0
For students, company representatives or hospital managers etc.
€ 0
The membership type best fitting for you will be selected automatically during the application process.
Reduced registration fees for ECR 2024:
Provided that ESR 2023 membership is activated and approved by August 31, 2023 (excl. "Members in Training Offer").
Reduced registration fees for ECR 2025:
Provided that ESR 2024 membership is activated and approved by August 31, 2024.