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

On Artificial Intelligence: An interview with Brendan Kelly

This week, we were extremely delighted to dive into the topic of artificial intelligence in radiology with Brendan Kelly. With a passion for AI, Kelly is currently an AI and Paediatric Radiology Fellow at Great Ormond Street Hospital for Children NHS Foundation Trust, a 2024 NDTP Dr. Richard Steevens Fellow, and an ESOR Fellow in AI and Paediatric Radiology. In

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Predictive potential of intratumoral and multiregion peritumoral radiomics

This study published in Insights into Imaging highlighted the potential of a multiparametric MRI-based radiomic model that integrated intratumoral and peritumoral features as a tool to predict differentiation in hepatocellular carcinoma (HCC). The authors found that the IntraPeri model showed an outstanding ability to predict individualized HCC differentiation through integrating intratumoral and optimal peritumoral features. Key points: Article: Multiparametric MRI-based

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On Artificial Intelligence: An interview with Michail Klontzas

The ESR’s AI blog was honored to speak with Michail Klontzas this week, to add to our growing series “On Artificial Intelligence”. Klontzas is currently an Assistant Professor of Radiology at the University of Crete in Heraklion, Greece, as well as an Editorial Board Member for the ESR’s flagship journal, European Radiology, in the Musculoskeletal section. Klontzas has a wealth

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AI can generate a scientific paper from scratch that can survive the peer-review process

In our latest exploration, we embarked on a journey to test the resilience of the peer-review systemagainst the ever-growing influence of AI in scientific literature. Alongside my colleague, weconceived a purely fictional MRI technique—Magnetic Resonance Audiometry (MRA)—and askedan AI model to generate an entire manuscript around it. The result? A complete, technically robustresearch paper, complete with equations, references, and even

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On Artificial Intelligence: An interview with Susan Shelmerdine

We were delighted to speak with Susan Shelmerdine this week for our interview series, “On Artificial Intelligence”. Among Shelmerdine’s many accolades are her roles as the Chairperson for the Artificial Intelligence Taskforce at the European Society of Paediatric Radiology as well as the prestigious Roentgen Professorship at The Royal College of Radiologists. Join us as we do a deep dive

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Automatic segmentation of fat metaplasia on sacroiliac joint MRI using deep learning

The authors of this study developed a deep learning model used for segmenting fat metaplasia (FM) on sacroiliac joint (SIJ) MRI with the additional aim of utilizing the deep learning model to classify axial spondyloarthritis (axSpA) and non-axSpA. They were able to conclude that the deep learning model could automatically and accurately segment FM on SIJ MRI, helping to increase

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On Artificial Intelligence: An interview with Daniel Pinto dos Santos

This week we spoke to Daniel Pinto dos Santos, Deputy Editor at the European Society of Radiology’s flagship journal, European Radiology, and a Board Member at the European Society of Medical Imaging Informatics (EuSoMII). Pinto dos Santos is currently a Senior Radiologist at the University Hospital Cologne and University Hospital Frankfurt in Germany. What is your background/experience with artificial intelligence

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Predicting microvascular invasion in small (≤ 5 cm) HCC using radiomics-based peritumoral analysis

This study assessed the predictive capacity of CT-enhanced radiomics models when determining microvascular invasion (MVI) for isolated hepatocellular carcinoma (HCC). The radiomics model was shown to be a promising noninvasive biomarker for preoperatively predicting MVI in individuals with a solitary HCC ≤ 5 cm and has applications in shaping personalized treatment policies. Key points: Article: Predicting microvascular invasion in small (≤ 5 cm)

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How do AI markings on screening mammograms correspond to cancer location?

This retrospective study compared the location of artificial intelligence (AI) markings on screening mammograms with cancer location on diagnostic mammograms and found that the AI markings corresponded to cancer location for all screen-detected cancers and 78% of the interval cancers with a high AI score. Key points: Article: How do AI markings on screening mammograms correspond to cancer location? An

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Enhancing recurrence risk prediction for bladder cancer using multi-sequence MRI radiomics

This study aimed to develop a radiomics-clinical nomogram using multi-sequence MRI to predict recurrence-free survival (RFS) in patients with bladder cancer (BCa). Using a retrospective cohort of 229 BCa patients, the authors determined that the radiomics-clinical nomogram was able to effectively assess BCa recurrence risk, outperforming both the radiomics model and the clinical model. Key points: Article: Enhancing recurrence risk

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  • 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 ESR journals 4
  • Updates on offers & events through our newsletters
  • Exclusive access to the ESR feed in Juisci

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Footnotes:

01

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

Reduced registration fees for ECR 2026:
Provided that ESR 2025 membership is activated and approved by August 31, 2025.

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.