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:

Latest posts

A deep learning framework for intracranial aneurysms automatic segmentation and detection on magnetic resonance T1 images

This study featured a design of a deep learning-based framework for the automatic segmentation of intracranial aneurysms (IAs) on MR T1 images while also testing the robustness and performance of the framework. The authors were able to conclude that their deep learning framework could effectively detect and segment IAs using clinical routine T1 sequences, which offers potential in improving the

Read More →

Evaluating Radiomics Research Reporting Assessment Tools to Improve Quality and Generalizability

As computational capabilities in healthcare continue to advance, the realm of texture analysis within medical imaging, known as radiomics, offers a promising avenue for uncovering novel imaging biomarkers aiding precision medicine [1].Nevertheless, clinical translation faces significant hurdles, primarily stemming from the heterogeneity of research questions and inconsistent quality of radiomics reporting, leading to a scarcity of studies that are comparable,

Read More →

Complexities of deep learning-based undersampled MR image reconstruction

Recent advances in AI have led to deep learning-based MR undersampled image reconstruction methods showing more speed-ups compared to traditional algorithms. MR undersampling is an excellent way to reduce scan time but can negatively impact image quality. Our literature review aims to inform a broader audience about this complex topic. This highly multidisciplinary science requires the informed input of many

Read More →

Unleashing the power of data in radiology: A look ahead

Peering into the future of radiology, we find ourselves at an exciting crossroads. The past year has seen language-based foundation models disrupt the status quo, offering a tantalising glimpse into new possibilities for data accessibility. Yet we still face a huge challenge: a wealth of valuable data remains locked away in free-text reports. But what if we could unlock this

Read More →

Predicting tertiary lymphoid structures status of ICC patients using CT radiomics

The authors of this study used preoperative CT radiomics in order to predict the tertiary lymphoid structures (TLSs) status and recurrence-free survival (RFS) of intrahepatic cholangiocarcinoma (ICC) patients. Enhanced CT images from a total of 116 ICC patients were included when using the radiomics model. The study results showed that the radiomics nomogram displayed better performance in predicting TLSs than

Read More →

Ready for testing artificial intelligence in radiology clinical practice

In the near future, I believe AI support systems will play a crucial role in the daily practice of radiologic reading. Radiologists are faced with an ever-increasing number of examinations and it remains vital to identify urgent cases as quickly as possible. An initial certified support system on the market has reported interesting performance data that proved the positive effect

Read More →

Reproducibility of radiomics quality score: an intra- and inter-rater reliability study

The rapidly evolving field of radiomics research holds the potential to revolutionize medicine by transforming diagnostic images into quantifiable data. Assessing the quality of radiomics research is challenging and requires reliable tools for standardization. Our results, published in European Radiology, have revealed some room for improvement regarding the reproducibility of the widely used Radiomics Quality Score (RQS). We recruited multiple

Read More →

MRI-based radiomics models show promise in clinical decision-making in spinal metastases patients

The aim of this study was to extract radiomics features from MRI using various machine learning algorithms which would then be integrated with clinical features to build response prediction models for spinal metastases patients who were undergoing stereotactic body radiotherapy (SBRT). The authors found that the MRI-based radiomics models showed valuable predictive capability for treatment outcomes regarding spinal metastases patients

Read More →

Implementing AI in breast imaging: challenges to turn the gadget into gain

In healthcare, the implementation of artificial intelligence (AI) is rapidly gaining momentum with breast imaging being no exception, or rather a poster child case. Numerous clinical indications intuitively lend themselves to AI enhancement. While the adoption of broad AI in clinical breast imaging practice has been more or less a silent revolution – it is already widely used for invite

Read More →

New radiomics model to predict the Leibovich risk groups for ccRCC patients

This study developed and validated a triphasic CT-based radiomics model, which incorporated radiomics features and significant clinical factors, for preoperative risk stratification of patients with localized clear cell renal cell carcinoma (ccRCC). The model showed a favorable performance in preoperatively predicting the Leibovich low-risk and intermediate-high-risk groups in localized ccRCC patients. The authors determined that this model can be used

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.

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 
  • Content e-mails for all ESR journals4
  • 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.

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 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.

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.

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.