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mammography

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-19interviewneural networksmammographydiagnostic imagingtomographybreast cancerMDCTworkflowradiography

Latest posts

Differentiating lesions presenting as calcifications with AI

European Radiology October 2022

The authors of this study aimed to evaluate how artificial intelligence computer-aided detection (AI-CAD) differentiates lesions presenting as calcifications, subsequently comparing its performance to that of an experienced breast radiologist. The authors discovered that AI-CAD showed similar diagnostic performances to the radiologists regarding calcifications detected in mammography. Key points Among calcifications with same morphology or BI-RADS assessment, those with positive

Read More →

Possible strategies for use of AI in screen-reading of mammograms

Marthe Larsen August 2022

After publishing the overall performance results of an AI system in Radiology (Artificial Intelligence Evaluation of 122,969 Mammography Examinations from a Population-based Screening Program), we explored different possible strategies for using AI in the screen-reading of mammograms. We presented estimated cancer detection rates for 11 different possible ways of implementing AI mammography screening. However, with different thresholds for selecting cases

Read More →

Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study

European Radiology November 2021

In this multi-reader, multi-case study, the authors aimed to investigate whether an artificial intelligence (AI) support system could help to increase the accuracy of breast radiologists reading wide-angle digital breast tomosynthesis (DBT). The study was performed using 240 bilateral DBT exams, with the exams interpreted by 18 radiologists with and without AI support. The authors found that the radiologists improved

Read More →

The promising possibility of using AI in mammography screening

Kristina Lång March 2021

In two recent publications in European Radiology, we have addressed two, of several, challenges with mammography screening. Firstly, the vast majority of screen exams are normal, which is resource-demanding, especially in the double-reading setting; and secondly, we miss cancer that can be particularly aggressive, later appearing as interval cancer. To understand if artificial intelligence (AI) can identify normal exams, we

Read More →

Artificial Intelligence to Help Radiologists in the Early Detection of Breast Cancer with Mammography and Breast Tomosynthesis

ESR December 2020

During the COVID-19 pandemic, routine breast cancer screening is largely being put on hold in many countries. Although it is not directly related, Sars-CoV-2 will have an effect on breast cancer screening and care. Having a closer look to Germany for instance, letters inviting women to screening were suspended until April, 30th.* The enormous decline in breast cancer screening is

Read More →

AI in Risk-Based Breast Screening

ESR November 2020

Artificial intelligence tools and technology are becoming more ingrained in the radiological discipline, but only recently in breast imaging, more specifically mammography and breast screening. Dr. Ritse Mann discussed with us the impact that AI is having on breast screening techniques and workflow, the current role it plays in hospitals and as an assistant to radiologists, and its future in

Read More →

Radiomics nomogram of contrast-enhanced spectral mammography for prediction of axillary lymph node metastasis in breast cancer: a multicenter study

European Radiology October 2020

The aim of this retrospective study was to establish and validate a radiomics nomogram that was based on contrast-enhanced spectral mammography (CESM) for the prediction of axillary lymph node (ALN) metastasis in breast cancer. The authors found that the CESM-based radiomics nomogram showed good application prospects in the preoperative prediction of ALN metastasis in breast cancer. Key points The CESM-based

Read More →

AI for reading screening mammograms: the need for circumspection

Philippe Autier July 2020

AI is viewed as an emerging technology for reading screening mammograms. However, most studies done so far have adopted retrospective designs that cannot fully appreciate the added value and limitations of AI technologies (Autier et al, Eur Radiol 2020, Apr 21). For instance, these studies cannot inform on numbers and results of biopsies that would have been done following a

Read More →

Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification

European Radiology February 2020

The authors of this study evaluated the impact of utilizing digital breast tomosynthesis (DBT) and/or full-field digital mammography (FFDM), and different transfer learning strategies, on deep convolutional neural network (DCNN)-based mass classification for breast cancer. The authors found that integrating DBT and FFDM in DCNN training helps to enhance breast mass classification accuracy. Key points Transfer learning facilitates mass classification

Read More →

Fully Interlinked for Rapid Data Exchange in Mammography

ESR January 2020

In the region of southern Denmark, a broad network of hospitals provides medical services for the 1.2 million residents of South Jutland and the island of Funen. A mammography screening program for women ranging in age from 50 to 69 has been running there for 25 years. More than 100,000 women are called in for an examination every year, and

Read More →

Differentiating lesions presenting as calcifications with AI

European Radiology October 2022

The authors of this study aimed to evaluate how artificial intelligence computer-aided detection (AI-CAD) differentiates lesions presenting as calcifications, subsequently comparing its performance to that of an experienced breast radiologist. The authors discovered that AI-CAD showed similar diagnostic performances to the radiologists regarding calcifications detected in mammography. Key points Among calcifications with same morphology or BI-RADS assessment, those with positive

Read More →

Possible strategies for use of AI in screen-reading of mammograms

Marthe Larsen August 2022

After publishing the overall performance results of an AI system in Radiology (Artificial Intelligence Evaluation of 122,969 Mammography Examinations from a Population-based Screening Program), we explored different possible strategies for using AI in the screen-reading of mammograms. We presented estimated cancer detection rates for 11 different possible ways of implementing AI mammography screening. However, with different thresholds for selecting cases

Read More →

Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study

European Radiology November 2021

In this multi-reader, multi-case study, the authors aimed to investigate whether an artificial intelligence (AI) support system could help to increase the accuracy of breast radiologists reading wide-angle digital breast tomosynthesis (DBT). The study was performed using 240 bilateral DBT exams, with the exams interpreted by 18 radiologists with and without AI support. The authors found that the radiologists improved

Read More →

The promising possibility of using AI in mammography screening

Kristina Lång March 2021

In two recent publications in European Radiology, we have addressed two, of several, challenges with mammography screening. Firstly, the vast majority of screen exams are normal, which is resource-demanding, especially in the double-reading setting; and secondly, we miss cancer that can be particularly aggressive, later appearing as interval cancer. To understand if artificial intelligence (AI) can identify normal exams, we

Read More →

Artificial Intelligence to Help Radiologists in the Early Detection of Breast Cancer with Mammography and Breast Tomosynthesis

ESR December 2020

During the COVID-19 pandemic, routine breast cancer screening is largely being put on hold in many countries. Although it is not directly related, Sars-CoV-2 will have an effect on breast cancer screening and care. Having a closer look to Germany for instance, letters inviting women to screening were suspended until April, 30th.* The enormous decline in breast cancer screening is

Read More →

AI in Risk-Based Breast Screening

ESR November 2020

Artificial intelligence tools and technology are becoming more ingrained in the radiological discipline, but only recently in breast imaging, more specifically mammography and breast screening. Dr. Ritse Mann discussed with us the impact that AI is having on breast screening techniques and workflow, the current role it plays in hospitals and as an assistant to radiologists, and its future in

Read More →

Radiomics nomogram of contrast-enhanced spectral mammography for prediction of axillary lymph node metastasis in breast cancer: a multicenter study

European Radiology October 2020

The aim of this retrospective study was to establish and validate a radiomics nomogram that was based on contrast-enhanced spectral mammography (CESM) for the prediction of axillary lymph node (ALN) metastasis in breast cancer. The authors found that the CESM-based radiomics nomogram showed good application prospects in the preoperative prediction of ALN metastasis in breast cancer. Key points The CESM-based

Read More →

AI for reading screening mammograms: the need for circumspection

Philippe Autier July 2020

AI is viewed as an emerging technology for reading screening mammograms. However, most studies done so far have adopted retrospective designs that cannot fully appreciate the added value and limitations of AI technologies (Autier et al, Eur Radiol 2020, Apr 21). For instance, these studies cannot inform on numbers and results of biopsies that would have been done following a

Read More →

Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification

European Radiology February 2020

The authors of this study evaluated the impact of utilizing digital breast tomosynthesis (DBT) and/or full-field digital mammography (FFDM), and different transfer learning strategies, on deep convolutional neural network (DCNN)-based mass classification for breast cancer. The authors found that integrating DBT and FFDM in DCNN training helps to enhance breast mass classification accuracy. Key points Transfer learning facilitates mass classification

Read More →

Fully Interlinked for Rapid Data Exchange in Mammography

ESR January 2020

In the region of southern Denmark, a broad network of hospitals provides medical services for the 1.2 million residents of South Jutland and the island of Funen. A mammography screening program for women ranging in age from 50 to 69 has been running there for 25 years. More than 100,000 women are called in for an examination every year, and

Read More →

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Footnotes:

01

Reduced registration fees for ECR 2024:
Provided that ESR 2023 membership is activated and approved by August 31, 2023 (excl. "Members in Training Offer").

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.