European Radiology

Machine learning and radiomics differentiate Crohn’s disease and ulcerative colitis

This retrospective study investigated whether volumetric visceral adipose tissue (VAT) features that were extracted using radiomics and three-dimensional...

European Radiology

14 hours ago

Deep learning image reconstruction improves DECT image quality

The purpose of this phantom study was the compare the image quality of a deep learning image reconstruction (DLIR) algorithm and conventional iterative...

European Radiology

2 weeks ago

Super-resolution application of GAN on brain time-of-flight MR angiography

This study aimed to develop a generative adversarial network (GAN) model to improve the image resolution of brain time-of-flight MR angiography (TOF-MRA), as...

European Radiology

1 month ago

Application of deep learning to improve image quality and reduce scan time

In this study, the image quality and diagnostic performance of conventional motion-corrected periodically rotated overlapping parallel line with enhanced...

European Radiology

2 months ago

Assessment of automatic rib fracture detection on chest CT using a deep learning algorithm

This retrospective study evaluated deep learning algorithms for the detection of automatic rib fracture on thoracic CT scans. The authors also aimed to...

European Radiology

3 months ago

Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in abdomen dual-energy CT

The aim of this study was to investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of...

European Radiology

5 months ago

Machine learning–based radiomics classifies parotid tumors using morphological MRI

This comparative study aimed to evaluate the effectiveness of machine learning models based on morphological MRI radiomics in the classification of parotid...

European Radiology

6 months ago

Deep Learning–driven classification of external DICOM studies for PACS archiving

The authors of this study used a deep learning-based approach, MOdality Mapping and Orchestration (MOMO), to deal with potential issues that are caused when...

European Radiology

7 months ago

AI system for detecting COVID-19 on chest radiographs in symptomatic patients

Due to the challenges associated with differentiating COVID-19 from the number of respiratory infections that can appear on chest radiographs (CXR), the...

European Radiology

7 months ago

Differentiating lesions presenting as calcifications with AI

The authors of this study aimed to evaluate how artificial intelligence computer-aided detection (AI-CAD) differentiates lesions presenting as calcifications,...

European Radiology

8 months ago