deep learning

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 osteoporosis. Furthermore, they aimed to develop a fully...

European Radiology

1 month ago

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 methodological aspects of machine learning (ML) in order to...

European Radiology

1 month ago

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 constructed the three dimensional (3D)-CNN model to predict pulmonary...

Masahiro Yanagawa

2 months ago

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, dual-energy CT (DECT) combined with a deep learning-based noise...

European Radiology

2 months ago

Deep learning–based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals

Chest radiographs (CRs) have long been used as one of the screening tests for pulmonary tuberculosis (TB). However, the interpretation of a large number of...

Chang Min Park

4 months ago

Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment

We use a previously validated artificial neural network to evaluate its performance in a much larger, subsequent, consecutive cohort. In the community, there...

David Bonekamp

5 months ago

From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans

In this retrospective study, the authors aimed to develop a fully automated artificial intelligence (AI) system to quantitatively assess the severity and...

European Radiology

6 months ago

Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration

The purpose of this study was to evaluate the calibration of a deep learning (DL) model in a diagnostic cohort, as well as to improve the model’s...

European Radiology

7 months ago

Emphysema quantification using low-dose computed tomography with deep learning-based kernel conversion comparison

This study used a sample of 131 participants who underwent low-dose computed tomography (LDCT) and standard-dose computed tomography (SDCT) to determine the...

European Radiology

8 months ago

Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography

In this study, the authors proposed a deep learning method for the detection and quantification of pneumothorax in heterogeneous routine clinical data, which...

European Radiology Experimental

9 months ago