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deep learning

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-19interviewmammographybreast cancerneural networksdiagnostic imagingtomographyMDCTradiographyworkflow

Latest posts

A novel AI model to distinguish benign from malignant ovarian tumors

Insights into Imaging July 2023

The authors of this study developed a CT-based artificial intelligence model with the ability to differentiate between benign and malignant ovarian tumors, showing high accuracy and specificity. In coordination with less-experienced radiologists, the model helped in the performance of ovarian tumor assessment, with applications to provide better therapeutic strategies for patients with ovarian tumors. Key points CT-based radiomics and deep

Read More →

Intelligent noninvasive meningioma grading using deep learning

European Radiology July 2023

The purpose of this study was to establish a robust interpretable deep learning (DL) model for the automatic noninvasive grading of meningiomas along with segmentation. Over 250 meningioma patients who underwent a preoperative brain MRI, including T2-weighted (T2) and contrast-enhanced T1-weighted (T1C) images, were included in the training set. The authors were able to determine that an interpretable multiparametric DL

Read More →

AI-aided software for detecting visible clinically significant prostate cancer on mpMRI

Insights into Imaging July 2023

This study seeks to determine if artificial intelligence (AI)-based software can improve radiologists’ performance when detecting clinically significant prostate cancer. Sixteen radiologists from four hospitals participated and were assigned 30 cases, half without AI and half with AI. The authors determined that the AI software improves the performance of radiologists by reducing false positive detection of prostate cancer patients while

Read More →

Using a multi-decoder water-fat separation neural network for liver PDFF estimation

European Radiology June 2023

The authors of this study proposed a multi-task U-Net-based architecture to jointly estimate water-only and fat-only images. This approach allowed for the improvement in the estimation of water-fat images, enabling a reduction of the necessary echoes to achieve an accurate proton density fat fraction (PDFF) quantification. The proposed method was shown to be a reliable liver fat quantification tool for

Read More →

Hepatic steatosis increases liver volume

Seung Soo Lee June 2023

Our recent research published in European Radiology aimed to evaluate the impact of hepatic steatosis (HS) on liver volume by conducting a retrospective analysis of 1,038 living liver donors. We measured liver volume on gadoxetic acid-enhanced hepatobiliary phase MR images and proton density fat fraction (PDFF). Our results showed that HS leads to a 4.4% increase in liver volume per

Read More →

Covid-19 early detection: Neural Networks vs. Radiologists

Insights into Imaging May 2023

The COVID-19 pandemic not only made an impact on the discipline of radiology as a whole but also on how we use specific tools in its detection. This was especially seen in the role of chest radiography when it was utilized as a diagnostic tool at the beginning of the pandemic “when microbiological resources were scarce,” evolving into its use

Read More →

Deep learning image reconstruction improves DECT image quality

European Radiology May 2023

The purpose of this phantom study was the compare the image quality of a deep learning image reconstruction (DLIR) algorithm and conventional iterative reconstruction (IR) algorithms in dual-energy CT (DECT) as well as assess the impact that these algorithms have on radiomics robustness. The authors determined that the new DLIR algorithm does in fact improve the quality of DECT images

Read More →

AI for prostate MRI: open datasets, available applications, and grand challenges

European Radiology Experimental April 2023

This narrative review provides an overview of the current state-of-the-art artificial intelligence (AI) applications for prostate MRI by focusing on open datasets, commercially and publically available AI systems, and challenges. The authors state that large amounts of research are still required in order to successfully utilize AI in the whole prostate pathway. Due to the rapidly growing field, continuous up-to-date

Read More →

Application of deep learning to improve image quality and reduce scan time

European Radiology April 2023

In this study, the image quality and diagnostic performance of conventional motion-corrected periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) MRI sequences was compared with post-processed PROPELLER MRI sequences using deep learning (DL)-based reconstructions. The authors found that the accelerated PROPELLER sequences with DL post-processing showed superior image quality and higher diagnostic confidence when compared to conventional PROPELLER sequences.

Read More →

Tasks for AI in prostate MRI

European Radiology Experimental March 2023

The authors of this narrative review aimed to introduce quality metrics for emerging artificial intelligence (AI) papers, such as the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) and Field-Weighted Citation Impact (FWCI). Furthermore, the study dives into some of the top AI models for segmentation, detection, and classification, while concluding that prospective studies with multi-center design will need to

Read More →

A novel AI model to distinguish benign from malignant ovarian tumors

Insights into Imaging July 2023

The authors of this study developed a CT-based artificial intelligence model with the ability to differentiate between benign and malignant ovarian tumors, showing high accuracy and specificity. In coordination with less-experienced radiologists, the model helped in the performance of ovarian tumor assessment, with applications to provide better therapeutic strategies for patients with ovarian tumors. Key points CT-based radiomics and deep

Read More →

Intelligent noninvasive meningioma grading using deep learning

European Radiology July 2023

The purpose of this study was to establish a robust interpretable deep learning (DL) model for the automatic noninvasive grading of meningiomas along with segmentation. Over 250 meningioma patients who underwent a preoperative brain MRI, including T2-weighted (T2) and contrast-enhanced T1-weighted (T1C) images, were included in the training set. The authors were able to determine that an interpretable multiparametric DL

Read More →

AI-aided software for detecting visible clinically significant prostate cancer on mpMRI

Insights into Imaging July 2023

This study seeks to determine if artificial intelligence (AI)-based software can improve radiologists’ performance when detecting clinically significant prostate cancer. Sixteen radiologists from four hospitals participated and were assigned 30 cases, half without AI and half with AI. The authors determined that the AI software improves the performance of radiologists by reducing false positive detection of prostate cancer patients while

Read More →

Using a multi-decoder water-fat separation neural network for liver PDFF estimation

European Radiology June 2023

The authors of this study proposed a multi-task U-Net-based architecture to jointly estimate water-only and fat-only images. This approach allowed for the improvement in the estimation of water-fat images, enabling a reduction of the necessary echoes to achieve an accurate proton density fat fraction (PDFF) quantification. The proposed method was shown to be a reliable liver fat quantification tool for

Read More →

Hepatic steatosis increases liver volume

Seung Soo Lee June 2023

Our recent research published in European Radiology aimed to evaluate the impact of hepatic steatosis (HS) on liver volume by conducting a retrospective analysis of 1,038 living liver donors. We measured liver volume on gadoxetic acid-enhanced hepatobiliary phase MR images and proton density fat fraction (PDFF). Our results showed that HS leads to a 4.4% increase in liver volume per

Read More →

Covid-19 early detection: Neural Networks vs. Radiologists

Insights into Imaging May 2023

The COVID-19 pandemic not only made an impact on the discipline of radiology as a whole but also on how we use specific tools in its detection. This was especially seen in the role of chest radiography when it was utilized as a diagnostic tool at the beginning of the pandemic “when microbiological resources were scarce,” evolving into its use

Read More →

Deep learning image reconstruction improves DECT image quality

European Radiology May 2023

The purpose of this phantom study was the compare the image quality of a deep learning image reconstruction (DLIR) algorithm and conventional iterative reconstruction (IR) algorithms in dual-energy CT (DECT) as well as assess the impact that these algorithms have on radiomics robustness. The authors determined that the new DLIR algorithm does in fact improve the quality of DECT images

Read More →

AI for prostate MRI: open datasets, available applications, and grand challenges

European Radiology Experimental April 2023

This narrative review provides an overview of the current state-of-the-art artificial intelligence (AI) applications for prostate MRI by focusing on open datasets, commercially and publically available AI systems, and challenges. The authors state that large amounts of research are still required in order to successfully utilize AI in the whole prostate pathway. Due to the rapidly growing field, continuous up-to-date

Read More →

Application of deep learning to improve image quality and reduce scan time

European Radiology April 2023

In this study, the image quality and diagnostic performance of conventional motion-corrected periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) MRI sequences was compared with post-processed PROPELLER MRI sequences using deep learning (DL)-based reconstructions. The authors found that the accelerated PROPELLER sequences with DL post-processing showed superior image quality and higher diagnostic confidence when compared to conventional PROPELLER sequences.

Read More →

Tasks for AI in prostate MRI

European Radiology Experimental March 2023

The authors of this narrative review aimed to introduce quality metrics for emerging artificial intelligence (AI) papers, such as the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) and Field-Weighted Citation Impact (FWCI). Furthermore, the study dives into some of the top AI models for segmentation, detection, and classification, while concluding that prospective studies with multi-center design will need to

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.