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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:

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

Latest posts

T2-weighted MRI-based radiomics discriminati between benign and borderline epithelial ovarian tumors

Insights into Imaging May 2023

The authors of this study investigated whether radiomics based on T2-weighted MRI was able to discriminate between benign and borderline epithelial ovarian tumors (EOTs) preoperatively. They were able to show that it can provide critical diagnostic information in the discrimination between benign and borderline EOTs, showing that there is potential to aid personalized treatment options. Key points T2-weighted MRI-based radiomics

Read More →

Utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics

Insights into Imaging March 2023

The aim of this study was to provide an updated systematic review of radiomics in osteosarcoma, utilizing various databases such as PubMed, Embase, China National Knowledge Infrastructure, and more. Articles found in these databases were assessed by Radiomics Quality Score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement, Checklist for Artificial Intelligence in

Read More →

The effect of preprocessing filters on predictive performance in radiomics

Aydin Demircioğlu February 2023

In radiomics, the main goal is to extract quantitative features from medical data to train a predictive model using machine learning techniques. Contrary to statistics, radiomics is data-driven; thus, there is a certain tendency to use as many features as possible. To achieve this, preprocessing filters are often applied; for example, a Gaussian filter smooths the image and thus removes

Read More →

EuSoMII Radiomics Auditing Group Initiative: Review of RQS applications

Arnaldo Stanzione February 2023

When the Radiomics Quality Score (RQS) was presented to the scientific community back in 2017, its authors aimed to introduce a tool for a rapid and effective evaluation of radiomics studies’ scientific/clinical merit. Conceived as a quality seal to be published alongside presented results and newly proposed radiomics models, the RQS has instead mostly been adopted by researchers as a

Read More →

Using parametric feature maps to enhance the stability of CT radiomics

Laura Jensen January 2023

It is known that the reproducibility of radiomic features is influenced by myriad factors, one of which is the size of the segmented volume. We hypothesized that parametric maps calculated with a fixed voxel size could address this issue. To test the hypothesis, we conducted a phantom study and could show that the stability across different volumes of interest sizes

Read More →

The latest developments in radiomics and AI may help against prostate cancer

European Radiology Experimental September 2022

The authors of this systematic review explored the currently available literature on artificial intelligence (AI) and radiomics applied to molecular imaging of prostate cancer. Due to the great promise that nuclear medicine holds regarding improving the quality of life for prostate cancer patients, this study looks at the myriad areas in which AI and radiomics can positively be applied to

Read More →

Metadata Models: The position of the AI for Health Imaging (AI4HI) network

European Radiology Experimental September 2022

Due to the enormous amount of imaging data that is becoming available, there is a wide range of possible improvements that can be provided by artificial intelligence (AI) algorithms in clinical care covering diagnosis and decision support. Therefore, it is crucial how we proceed in managing and handling this data, e.g. medical images, and to define which metadata must be

Read More →

The potential of texture analysis for breast density classification

European Radiology Experimental August 2022

Breast cancer continues to be the most commonly diagnosed cancer among women with over 2 million new cases per year worldwide. One important independent risk factor for developing breast cancer is breast density (BD). Epidemiological studies show that women with dense tissue may have an increased risk of developing breast cancer by 2-6 times when compared to women with less

Read More →

Radiomic features of breast parenchyma

Insights into Imaging July 2022

The object of this study was to assess the similarities and differences of radiomics features on full field digital mammography (FFDM) in FOR PROCESSING and FOR PRESENTATION data. The authors aimed to address the problem using an enlarged set of texture radiomic features, dense/non-dense areas comparison and a new manufacturer, concluding that texture features from FOR PROCESSING mammograms were the

Read More →

Can radiomics signatures predict tumor reponse of patients treated with chemotherapy and targeted therapy?

European Radiology May 2022

The authors of this retrospective study had the goal of evaluating the effectiveness of radiomics signatures in order to predict the tumor response of non-small cell lung cancer (NSCLC) patients who were treated with first-line chemotherapy, targeted therapy, or a combination of the two. The authors determined that radiomics signatures based on pre-treatment CT scans can accurately predict tumor response

Read More →

T2-weighted MRI-based radiomics discriminati between benign and borderline epithelial ovarian tumors

Insights into Imaging May 2023

The authors of this study investigated whether radiomics based on T2-weighted MRI was able to discriminate between benign and borderline epithelial ovarian tumors (EOTs) preoperatively. They were able to show that it can provide critical diagnostic information in the discrimination between benign and borderline EOTs, showing that there is potential to aid personalized treatment options. Key points T2-weighted MRI-based radiomics

Read More →

Utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics

Insights into Imaging March 2023

The aim of this study was to provide an updated systematic review of radiomics in osteosarcoma, utilizing various databases such as PubMed, Embase, China National Knowledge Infrastructure, and more. Articles found in these databases were assessed by Radiomics Quality Score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement, Checklist for Artificial Intelligence in

Read More →

The effect of preprocessing filters on predictive performance in radiomics

Aydin Demircioğlu February 2023

In radiomics, the main goal is to extract quantitative features from medical data to train a predictive model using machine learning techniques. Contrary to statistics, radiomics is data-driven; thus, there is a certain tendency to use as many features as possible. To achieve this, preprocessing filters are often applied; for example, a Gaussian filter smooths the image and thus removes

Read More →

EuSoMII Radiomics Auditing Group Initiative: Review of RQS applications

Arnaldo Stanzione February 2023

When the Radiomics Quality Score (RQS) was presented to the scientific community back in 2017, its authors aimed to introduce a tool for a rapid and effective evaluation of radiomics studies’ scientific/clinical merit. Conceived as a quality seal to be published alongside presented results and newly proposed radiomics models, the RQS has instead mostly been adopted by researchers as a

Read More →

Using parametric feature maps to enhance the stability of CT radiomics

Laura Jensen, Damon Kim, Sebastian Nagel January 2023

It is known that the reproducibility of radiomic features is influenced by myriad factors, one of which is the size of the segmented volume. We hypothesized that parametric maps calculated with a fixed voxel size could address this issue. To test the hypothesis, we conducted a phantom study and could show that the stability across different volumes of interest sizes

Read More →

The latest developments in radiomics and AI may help against prostate cancer

European Radiology Experimental September 2022

The authors of this systematic review explored the currently available literature on artificial intelligence (AI) and radiomics applied to molecular imaging of prostate cancer. Due to the great promise that nuclear medicine holds regarding improving the quality of life for prostate cancer patients, this study looks at the myriad areas in which AI and radiomics can positively be applied to

Read More →

Metadata Models: The position of the AI for Health Imaging (AI4HI) network

European Radiology Experimental September 2022

Due to the enormous amount of imaging data that is becoming available, there is a wide range of possible improvements that can be provided by artificial intelligence (AI) algorithms in clinical care covering diagnosis and decision support. Therefore, it is crucial how we proceed in managing and handling this data, e.g. medical images, and to define which metadata must be

Read More →

The potential of texture analysis for breast density classification

European Radiology Experimental August 2022

Breast cancer continues to be the most commonly diagnosed cancer among women with over 2 million new cases per year worldwide. One important independent risk factor for developing breast cancer is breast density (BD). Epidemiological studies show that women with dense tissue may have an increased risk of developing breast cancer by 2-6 times when compared to women with less

Read More →

Radiomic features of breast parenchyma

Insights into Imaging July 2022

The object of this study was to assess the similarities and differences of radiomics features on full field digital mammography (FFDM) in FOR PROCESSING and FOR PRESENTATION data. The authors aimed to address the problem using an enlarged set of texture radiomic features, dense/non-dense areas comparison and a new manufacturer, concluding that texture features from FOR PROCESSING mammograms were the

Read More →

Can radiomics signatures predict tumor reponse of patients treated with chemotherapy and targeted therapy?

European Radiology May 2022

The authors of this retrospective study had the goal of evaluating the effectiveness of radiomics signatures in order to predict the tumor response of non-small cell lung cancer (NSCLC) patients who were treated with first-line chemotherapy, targeted therapy, or a combination of the two. The authors determined that radiomics signatures based on pre-treatment CT scans can accurately predict tumor response

Read More →

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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

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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.
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For students, company representatives or hospital managers etc.

  • Content e-mails for all 3 ESR journals 4
  • Updates on offers & events through our newsletters

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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.