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liver

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

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 →

Precision of MRI radiomics features in the liver and HCC

European Radiology June 2022

The aim of this study, consisting of a population of 55 patients who underwent two repeat contrast-enhanced abdominal MRI exams within 1 month, was to assess the precision of MRI radiomics features in hepatocellular carcinoma (HCC) tumors and liver parenchyma. The authors determined that MRI radiomics features have acceptable repeatability in the liver and HCC when using the same MRI

Read More →

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

European Radiology Experimental November 2019

The authors of this study aimed to assess the performance of a convolutional neural network (CNN) algorithm to register cross-sectional liver imaging series and its performance to manual image registration. The study included three hundred fourteen patients who underwent gadoxetate disodium-enhanced magnetic resonance imaging (MRI) and were retrospectively selected. Key points Image registration across series can improve lesion co-localization and

Read More →

Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

European Radiology May 2019

Deep learning reconstruction (DLR) is a novel method of reconstruction that introduces deep convolutional neural networks into the reconstruction flow. The authors of this research examined the clinical applicability of abdominal ultra-high-resolution CT (U-HRCT) exams reconstructed with a new DLR and to compare it to hybrid and model-based iterative reconstruction (hybrid-IR, MBIR). Radiologists analysed and graded results from 46 patients

Read More →

Radiomics of liver MRI predict metastases in mice

European Radiology Experimental February 2019

This study aimed to investigate whether any texture features show a correlation with intrahepatic tumor growth before the metastasis is visible to the human eye. For the purposes of the study, eight mice were injected intraportally with syngeneic MC-38 colon cancer cells and two mice were injected with phosphate-buffered saline (sham controls). Magnetic resonance imaging (MRI) and texture analysis were

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 →

Precision of MRI radiomics features in the liver and HCC

European Radiology June 2022

The aim of this study, consisting of a population of 55 patients who underwent two repeat contrast-enhanced abdominal MRI exams within 1 month, was to assess the precision of MRI radiomics features in hepatocellular carcinoma (HCC) tumors and liver parenchyma. The authors determined that MRI radiomics features have acceptable repeatability in the liver and HCC when using the same MRI

Read More →

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

European Radiology Experimental November 2019

The authors of this study aimed to assess the performance of a convolutional neural network (CNN) algorithm to register cross-sectional liver imaging series and its performance to manual image registration. The study included three hundred fourteen patients who underwent gadoxetate disodium-enhanced magnetic resonance imaging (MRI) and were retrospectively selected. Key points Image registration across series can improve lesion co-localization and

Read More →

Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

European Radiology May 2019

Deep learning reconstruction (DLR) is a novel method of reconstruction that introduces deep convolutional neural networks into the reconstruction flow. The authors of this research examined the clinical applicability of abdominal ultra-high-resolution CT (U-HRCT) exams reconstructed with a new DLR and to compare it to hybrid and model-based iterative reconstruction (hybrid-IR, MBIR). Radiologists analysed and graded results from 46 patients

Read More →

Radiomics of liver MRI predict metastases in mice

European Radiology Experimental February 2019

This study aimed to investigate whether any texture features show a correlation with intrahepatic tumor growth before the metastasis is visible to the human eye. For the purposes of the study, eight mice were injected intraportally with syngeneic MC-38 colon cancer cells and two mice were injected with phosphate-buffered saline (sham controls). Magnetic resonance imaging (MRI) and texture analysis were

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
  • 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

€ 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
  • 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.
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 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.