AI Blog

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.

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Latest posts

Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics

In this study, the authors aimed to assess the potential of machine learning (ML) based on B-mode, shear-wave elastography (SWE), and dynamic contrast-enhanced ultrasound (DCE-US) radiomics for the localization of prostate cancer lesions using transrectal ultrasound. The authors were able to demonstrate the technical feasibility of multiparametric ML to improve upon single US modalities for the localization of prostate cancer.

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Looking outside the box: AI learning about the solar system, predicting lightning strikes, and women discussing bias in AI

This week in artificial intelligence (AI) news, we take a look at physicists in Switzerland who developed a neural network that is teaching itself about the laws of physics in our solar system, researchers using AI systems to predict when lightning will strike, and three women discussing how they approach bias in AI. In a recent article from Nature, physicists have

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Motion-corrected coronary calcium scores by a CNN: a robotic simulating study

The authors of this study aimed to classify motion-induced blurred images of calcified coronary plaques, in order to correct coronary calcium scored on non-triggered chest computed tomography (CT). They did so by using a deep convolutional neural network (CNN) which was trained using a selection of images of motion artifacts. Key points A deep CNN architecture trained by CT images

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Why I Stopped Worrying And Love The Intelligent Machine

The future will always be just that…until it becomes the present. That is especially true when the future involves science. What if science fiction has a way of turning – suddenly – into scientific fact? Like flying machines and spacecraft, one day they existed only in theory, and the next, they became a reality. At the annual meeting of the

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

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

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Looking outside the box: using AI to help elephants, tracking bird populations, and fighting food waste

This week in artificial intelligence (AI) news, we take a look at African parks using AI to fight poachers and help the declining elephant population, monitoring bird populations using deep learning, and how a company in the United Kingdom is using technology to combat food waste more efficiently. In this article from NPR, researchers in Africa are taking advantage of

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A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging

The aim of this study was to develop a supervised machine learning (ML) algorithm that would use diffusion-weighted imaging-derived radiomic features to predict median overall survival in patients with pancreatic ductal adenocarcinoma. Based on the evaluation of 132 patients, it was determined that the use of ML allowed the prediction of overall survival with high diagnostic accuracy. Key points Pancreatic

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Deep learning to convert unstructured CT pulmonary angiography reports into structured reports

We believe that the possibilities for artificial intelligence (AI) over the coming years will be limited only by our imagination. While there is a tremendous amount of warranted excitement for disease detection, characterization, and quantification with AI algorithms, less rousing but still valuable efforts can and should be made to improve operational efficiency and even reduce the growing problem of

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Looking outside the box: anxiety over future employment, tricking AI systems, and an autonomous journey across the Atlantic

This week in artificial intelligence (AI) news, we take a look at a poll showing the lack of confidence individuals have in their preparation for a world run by AI, the fragility of deep neural networks and how to fool them, and autonomously retracing the journey of the Mayflower. In a recent poll by Northeastern University and Gallup, a disconcerting

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MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma

This study integrated the clinical data and radiomics signature generated by a support vector machine to establish a radiomics nomogram for prediction of induction chemotherapy response and survival in nasopharyngeal carcinoma patients. The results proved that multiparametric MRI-based radiomics could be helpful for personalized risk stratification in patients receiving induction chemotherapy. Key points MRI Radiomics can predict IC response and

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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.

Reduced registration fees for ECR 2025:
Provided that ESR 2024 membership is activated and approved by August 31, 2024.

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European Radiology, Insights into Imaging, European Radiology Experimental.