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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.

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Back to main AI Blog

x-ray computed tomography

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 learningradiomicsmrix-ray computed tomographyai newsCOVID-19mammographyinterviewbreast cancerneural networksdiagnostic imagingtomographyMDCTworkflowradiography

Latest posts

Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives

European Radiology January 2021

This literature review summarizes the current status and evaluates the scientific reporting quality of radiomics research in the prediction of treatment response in non-small-cell lung cancer (NSCLC). The authors performed this literature review through a comprehensive literature search using the PubMed database, screening a total of 178 articles for eligibility. Key points The included studies reported several promising radiomic markers

Read More →

Motion-corrected coronary calcium scores by a CNN: a robotic simulating study

European Radiology November 2019

The authors of this study aimed to classify motion-induced blurred images of calcified coronary plaques, in order to correct coronary calcium scored on non-triggered chest computed tomography (CT). They did so by using a deep convolutional neural network (CNN) which was trained using a selection of images of motion artifacts. Key points A deep CNN architecture trained by CT images

Read More →

Deep learning to convert unstructured CT pulmonary angiography reports into structured reports

John Nance October 2019

We believe that the possibilities for artificial intelligence (AI) over the coming years will be limited only by our imagination. While there is a tremendous amount of warranted excitement for disease detection, characterization, and quantification with AI algorithms, less rousing but still valuable efforts can and should be made to improve operational efficiency and even reduce the growing problem of

Read More →

Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation

Richard Do September 2019

The goal of this study was to measure the reproducibility of radiomic features in pancreatic parenchyma and ductal adenocarcinomas in patients who underwent consecutive contrast-enhanced computed tomography (CECT) scans. A majority of features were not reproducible (as defined by a concordance correlation coefficient of greater than 0.9) when comparing their values across consecutive CECTs obtained within a two week period.

Read More →

Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives

European Radiology January 2021

This literature review summarizes the current status and evaluates the scientific reporting quality of radiomics research in the prediction of treatment response in non-small-cell lung cancer (NSCLC). The authors performed this literature review through a comprehensive literature search using the PubMed database, screening a total of 178 articles for eligibility. Key points The included studies reported several promising radiomic markers

Read More →

Motion-corrected coronary calcium scores by a CNN: a robotic simulating study

European Radiology November 2019

The authors of this study aimed to classify motion-induced blurred images of calcified coronary plaques, in order to correct coronary calcium scored on non-triggered chest computed tomography (CT). They did so by using a deep convolutional neural network (CNN) which was trained using a selection of images of motion artifacts. Key points A deep CNN architecture trained by CT images

Read More →

Deep learning to convert unstructured CT pulmonary angiography reports into structured reports

John Nance October 2019

We believe that the possibilities for artificial intelligence (AI) over the coming years will be limited only by our imagination. While there is a tremendous amount of warranted excitement for disease detection, characterization, and quantification with AI algorithms, less rousing but still valuable efforts can and should be made to improve operational efficiency and even reduce the growing problem of

Read More →

Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation

Richard Do September 2019

The goal of this study was to measure the reproducibility of radiomic features in pancreatic parenchyma and ductal adenocarcinomas in patients who underwent consecutive contrast-enhanced computed tomography (CECT) scans. A majority of features were not reproducible (as defined by a concordance correlation coefficient of greater than 0.9) when comparing their values across consecutive CECTs obtained within a two week period.

Read More →

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
  • Exclusive 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
  • 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 2024:
Provided that ESR 2023 membership is activated and approved by August 31, 2023.

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.