AI Blog

Deep learning–based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC

Of late, deep learning-based algorithms have been successfully applied to various medical imaging modalities, ranging from chest radiographs to head CT scans....

So Yeon Kim

Deep learning–based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC

Publications

Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT

The authors of this study aimed to develop and validate a combined radiomics-clinical model to predict malignancy of cerebral compression fractures on CT....

European Radiology

$Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT$

Publications

A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients

The authors of this study analyzed and compared the imaging workflow, radiation dose, and image quality for 127 adult COVID-19 patients who were examined...

European Radiology

A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients

Publications

An A.I. classifier derived from 4D radiomics of dynamic contrast-enhanced breast MRI data: potential to avoid unnecessary breast biopsies

In this retrospective study, the authors aimed to evaluate a temporally and spatially resolved (4D) radiomics approach to distinguish benign from malignant...

European Radiology

An A.I. classifier derived from 4D radiomics of dynamic contrast-enhanced breast MRI data: potential to avoid unnecessary breast biopsies

Deep learning–based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC

Of late, deep learning-based algorithms have been successfully applied to various medical imaging...

So Yeon Kim

1 week ago

Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT

The authors of this study aimed to develop and validate a combined radiomics-clinical model to...

European Radiology

2 weeks ago

$Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT$

A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients

The authors of this study analyzed and compared the imaging workflow, radiation dose, and image...

European Radiology

3 weeks ago

An A.I. classifier derived from 4D radiomics of dynamic contrast-enhanced breast MRI data: potential to avoid unnecessary breast biopsies

In this retrospective study, the authors aimed to evaluate a temporally and spatially resolved...

European Radiology

1 month ago

Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in algorithm training

Due to the noisy annotation quality of public training data and confounding thoracic tubes, the...

European Radiology

1 month ago

Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in algorithm training

Development and multicenter validation of a CT-based radiomics signature for predicting severe COVID-19 pneumonia

The authors of this study aimed to develop and validate a radiomics nomogram for the prompt...

European Radiology

1 month ago

Development and multicenter validation of a CT-based radiomics signature for predicting severe COVID-19 pneumonia

Radiomics approach for survival prediction in chronic obstructive pulmonary disease

The idea of quantification of disease severity of chronic obstructive pulmonary disease (COPD)...

Joon Beom Seo

2 months ago

Radiomics approach for survival prediction in chronic obstructive pulmonary disease

Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19

In this study, the authors aimed to develop and validate a machine learning model for the...

European Radiology

2 months ago

Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19

Radiology artificial intelligence, a systematic evaluation of methods (RAISE): a systematic review protocol

The review was prospectively registered on PROSPERO and adheres to the PRISMA protocols. We...

Brendan Kelly

2 months ago

Radiology artificial intelligence, a systematic evaluation of methods (RAISE): a systematic review protocol

Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks

In this study, the authors explored the application of deep learning in patients with primary...

European Radiology

2 months ago

Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks

How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts

In this article, the authors aimed to guide and inform the radiology community regarding key...

European Radiology

3 months ago

How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts

Diagnostic performance for pulmonary adenocarcinoma on CT: comparison of radiologists with and without three-dimensional convolutional neural network

Convolutional neural networks (CNNs) are often used in the area of image recognition. We...

Masahiro Yanagawa

3 months ago

Diagnostic performance for pulmonary adenocarcinoma on CT: comparison of radiologists with and without three-dimensional convolutional neural network

To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)

Artificial intelligence (AI) has certainly made impressive progress over the past few years....

Patrick Omoumi & Daniel Pinto dos Santos

3 months ago

To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)

Development of MR-based preoperative nomograms predicting DNA copy number subtype in lower grade gliomas with prognostic implication

The aim of this study was to determine the value of MR-based preoperative nomograms in predicting...

European Radiology

3 months ago

Development of MR-based preoperative nomograms predicting DNA copy number subtype in lower grade gliomas with prognostic implication

Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique

The authors of this study aimed to evaluate the image quality of low iodine concentration,...

European Radiology

3 months ago

Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique

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.

Welcome to the blog on Artificial Intelligence of the European Society of Radiology

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