European Radiology Experimental

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

2 weeks ago

Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach

The aim of this study was to evaluate whether machine learning algorithms allow for the prediction of Child-Pugh classification on clinical multiphase...

European Radiology Experimental

5 months ago

A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI

This preliminary study aimed to differentiate malignant from benign enhancing foci on breast MRI using radiomic signature. Forty-five patients were included...

European Radiology Experimental

8 months ago

A pilot study on the performance of machine learning appled to texture-analysis-derived features for breast lesion characterisation at ABUS

In this study, the authors aimed to determine whether features derived from texture analysis (TA) are able to distinguish between normal, benign, and...

European Radiology Experimental

11 months ago

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...

European Radiology Experimental

12 months ago

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...

European Radiology Experimental

12 months ago

Automatic segmentation and classification of breast lesions through identification of informative multiparametric PET/MRI features

The authors of this study recognized the potential of multiparametric positron emission tomography/magnetic resonance imaging (mpPET/MRI) for detecting and...

European Radiology Experimental

1 year ago

Applying 3D CNN to CTA source images to detect ischemic stroke

In this study, the authors investigated how feasible it was to use 3D convolutional neural networks (CNN) to detect ischemic stroke from computed tomography...

European Radiology Experimental

2 years ago

Is there a future for deep learning-based generative models in musculoskeletal radiology?

This article sought to investigate the potential of generative models in the field of MRI of the spine, and did so by performing clinically relevant benchmark...

European Radiology Experimental

2 years ago

Should AI be seen as a threat or an opportunity in medical imaging?

The aim of this narrative review is to take a broader look at the application of Artificial Intelligence (AI), primarily in medical imaging. The authors...

European Radiology Experimental

2 years ago