AI Blog

AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset

Our study included 519 screening chest radiographs (CXRs) from 294 patients enrolled in the National Lung Screening Trial (NLST) who either had proven to have...

Hyunsuk Yoo & Mannudeep Kalra & Subba Digumarthy

AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset

Publications

Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer’s disease: a preliminary study

Subjective cognitive decline (SCD) may be a preclinical stage of Alzheimer's disease (AD). For this preliminary study, the authors recruited one hundred ten...

European Radiology

Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer’s disease: a preliminary study

Publications

Fully automated pelvic bone segmentation in multiparametric MRI using a 3D convolutional neural network

The accurate skeleton segmentation with their semantic labels represents the initial step to achieve accurate prostate cancer bone metastases detection on DWI...

Xiaoying Wang

Fully automated pelvic bone segmentation in multiparametric MRI using a 3D convolutional neural network

Publications

Practice makes perfect: Using AR to simulate CT guided procedures

As a junior radiology trainee, when I was not in the reporting room or on the wards doing portable ultrasounds, I found learning CT procedures a daunting task...

Dimitri Amiras

Practice makes perfect: Using AR to simulate CT guided procedures

Publications

Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach

Performed between 2015 and 2018, the purpose of this study was to develop and validate a deep learning-based algorithm for the segmentation and quantification...

European Radiology

Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach

AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset

Our study included 519 screening chest radiographs (CXRs) from 294 patients enrolled in the...

Hyunsuk Yoo & Mannudeep Kalra & Subba Digumarthy

6 days ago

Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer’s disease: a preliminary study

Subjective cognitive decline (SCD) may be a preclinical stage of Alzheimer's disease (AD). For...

European Radiology

2 weeks ago

Fully automated pelvic bone segmentation in multiparametric MRI using a 3D convolutional neural network

The accurate skeleton segmentation with their semantic labels represents the initial step to...

Xiaoying Wang

3 weeks ago

Practice makes perfect: Using AR to simulate CT guided procedures

As a junior radiology trainee, when I was not in the reporting room or on the wards doing portable...

Dimitri Amiras

4 weeks ago

Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach

Performed between 2015 and 2018, the purpose of this study was to develop and validate a deep...

European Radiology

1 month ago

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

Although challenging to predict, early recognition of COVID-19 severity can help guide patient...

European Radiology

1 month ago

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

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

2 months ago

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

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 months 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 months ago

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

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

3 months ago

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

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

3 months 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

3 months 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

3 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

4 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

4 months ago

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

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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