European Radiology

Automated classification of solid renal masses on contrast-enhanced computed tomography images using convolutional neural network with decision fusion

The purpose of this study was to develop a deep learning-based method for the automated classification of renal cell carcinoma (RCC) from benign solid renal...

European Radiology

4 weeks ago

Optimal matrix size of chest radiographs for computer-aided detection on lung nodule or mass with deep learning

In this study, the authors retrospectively collected 2,088 abnormal and 352 normal chest radiographs from two institutions in order to investigate the optimal...

European Radiology

1 month ago

Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer

The purpose of this retrospective study was to develop and evaluate the performance of U-Net to determine whether U-Net-based deep learning could accurately...

European Radiology

2 months ago

Deep learning: definition and perspectives for thoracic imaging

The authors of this review aimed to provide definitions for understanding the methods of machine learning, deep learning, and convolutional neural networks...

European Radiology

2 months ago

A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images

In this study, the authors aimed to develop a deep learning-based artificial intelligence (AI) scheme in order to predict the likelihood of the ground-glass...

European Radiology

3 months ago

Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT

The authors of this study aimed to determine the diagnostic performance of a deep learning algorithm for the automated detection of small 18F-FDG-avid...

European Radiology

3 months ago

Test-retest reproducibility of a deep learning–based automatic detection algorithm for the chest radiograph

The authors of this retrospective study performed test-retest reproducibility analyses for a deep learning-based automatic detection algorithm (DLAD) using...

European Radiology

4 months ago

Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound

The aim of this study was to establish and validate an artificial intelligence-based radiomics strategy in order to predict personalized responses to...

European Radiology

4 months ago

Dual-energy CT–based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer

In this study, the authors aimed to build a dual-energy CT (DECT)-based deep learning radiomics nomogram that could be used for lymph node metastasis...

European Radiology

5 months ago

Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas?

In this study, the authors aimed to improve the prediction of patients’ prognosis of myxoid/round cell liposarcomas (MRC-LPS) using a radiomics...

European Radiology

5 months ago