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radiomics

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:

deep learningmachine learningmriradiomicsx-ray computed tomographyinterviewai newsmammographyCOVID-19diagnostic imagingneural networksbreast cancerbreast neoplasmsworkflowtomographyradiography

Latest posts

Image biomarkers and explainable AI

European Radiology Experimental February 2025

Feature extraction and selection in medical data are crucial for radiomics and image biomarker discovery, particularly using convolutional neural networks (CNNs). The process involves feature extraction, dimensionality reduction, and addressing the curse of dimensionality. While deep learning (DL) techniques perform well, handcrafted features are important for certain studies and need to be considered. Dataset size and diversity are also key

Read More →

Predictive potential of intratumoral and multiregion peritumoral radiomics

Insights into Imaging October 2024

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

Read More →

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

Insights into Imaging September 2024

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)

Read More →

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

Insights into Imaging September 2024

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

Read More →

CT-based radiomics combined with hematologic parameters for survival prediction

Insights into Imaging August 2024

This study aimed to investigate the prognostic significance of radiomics in conjunction with hematological parameters relating to the overall survival (OS) of patients diagnosed with esophageal squamous cell carcinoma (ESCC) after undergoing definitive chemoradiotherapy (dCRT). Utilizing radiomics and hematologic parameters, the authors were able to develop a prognostic model that enabled the prediction of OS in ESCC patients. This approach

Read More →

Sharing is Caring – Promoting Radiomics Research Transparency and Sustainability

Hyun Soo Ko June 2024

Radiomics, a rapidly growing and innovative field in medical imaging, extracts detailed features from medical scans that could play a pivotal future adjunct role in patient care. However, the clinical adoption of radiomics is stalled by significant research heterogeneity and reproducibility issues [1]. The complex radiomics pipeline, requiring multidisciplinary expertise, often lacks transparency regarding sharing crucial details like software tools

Read More →

Evaluating Radiomics Research Reporting Assessment Tools to Improve Quality and Generalizability

Hyun Soo Ko April 2024

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 →

Predicting tertiary lymphoid structures status of ICC patients using CT radiomics

Insights into Imaging April 2024

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 →

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

Tugba Akinci D’Antonoli March 2024

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 →

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

Insights into Imaging March 2024

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 →

Image biomarkers and explainable AI

European Radiology Experimental February 2025

Feature extraction and selection in medical data are crucial for radiomics and image biomarker discovery, particularly using convolutional neural networks (CNNs). The process involves feature extraction, dimensionality reduction, and addressing the curse of dimensionality. While deep learning (DL) techniques perform well, handcrafted features are important for certain studies and need to be considered. Dataset size and diversity are also key

Read More →

Predictive potential of intratumoral and multiregion peritumoral radiomics

Insights into Imaging October 2024

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

Read More →

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

Insights into Imaging September 2024

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)

Read More →

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

Insights into Imaging September 2024

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

Read More →

CT-based radiomics combined with hematologic parameters for survival prediction

Insights into Imaging August 2024

This study aimed to investigate the prognostic significance of radiomics in conjunction with hematological parameters relating to the overall survival (OS) of patients diagnosed with esophageal squamous cell carcinoma (ESCC) after undergoing definitive chemoradiotherapy (dCRT). Utilizing radiomics and hematologic parameters, the authors were able to develop a prognostic model that enabled the prediction of OS in ESCC patients. This approach

Read More →

Sharing is Caring – Promoting Radiomics Research Transparency and Sustainability

Hyun Soo Ko June 2024

Radiomics, a rapidly growing and innovative field in medical imaging, extracts detailed features from medical scans that could play a pivotal future adjunct role in patient care. However, the clinical adoption of radiomics is stalled by significant research heterogeneity and reproducibility issues [1]. The complex radiomics pipeline, requiring multidisciplinary expertise, often lacks transparency regarding sharing crucial details like software tools

Read More →

Evaluating Radiomics Research Reporting Assessment Tools to Improve Quality and Generalizability

Hyun Soo Ko, Kevin Tran April 2024

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 →

Predicting tertiary lymphoid structures status of ICC patients using CT radiomics

Insights into Imaging April 2024

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 →

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

Tugba Akinci D’Antonoli March 2024

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 →

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

Insights into Imaging March 2024

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.

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 
  • 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.
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 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 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.