European Radiology

Radiation dose in pregnancy

Due to the high radiosensitivity of the fetus and embryo, diagnostic imaging procedures for pregnant patients raise health concerns. Therefore, the authors of...

European Radiology

2 months ago

Deep learning to differentiate parkinsonian disorders separately using single midsagittal MR imaging

In an attempt to determine whether deep learning with the convolutional neural networks (CNN) can be used for identifying parkinsonian disorder on MRI, the...

European Radiology

2 months ago

Are semi-automated software programs designed for adults accurate for the identification of vertebral fractures in children?

The goal of this study was to test if using AVERT™ (a 33-point semi-automated program developed for VF diagnosis in adults) is better for morphometric...

European Radiology

3 months ago

Machine learning classifiers vs. Experienced radiologists: Predicting Gleason pattern 4 prostate cancer

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

European Radiology

3 months ago

Using radiomics for the preoperative estimation of pathological grade in bladder cancer tumors

The goal of this study was to develop and authenticate an MRI-based radiomics strategy for the preoperative estimation of pathological grade in bladder cancer...

European Radiology

3 months ago

MRI radiomics in categorizing ovarian masses and predicting clinical outcome: a preliminary study

This study aimed to assess whether MRI radiomics can categorize ovarian masses and to determine the association between MRI radiomics and survival among...

European Radiology

4 months ago

Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

Deep learning reconstruction (DLR) is a novel method of reconstruction that introduces deep convolutional neural networks into the reconstruction flow. The...

European Radiology

4 months ago

Taking artificial intelligence out of the black box: An “interpretable” deep learning system for liver tumour diagnosis

Convolutional neural networks (CNN) have demonstrated the potential to become effective and accurate decision support tools for radiologists. A major barrier...

European Radiology

4 months ago

CT reconstruction algorithms affect histogram and texture analysis: evidence for liver parenchyma, focal solid liver lesions, and renal cysts

The aim of this study was to determine the effects of different reconstruction algorithms on histogram and texture features in different targets. The authors...

European Radiology

5 months ago

Differentiation of clear cell and non-clear cell renal cell carcinomas by all-relevant radiomics features from multiphase CT: a VHL mutation perspective

The main goal of this retrospective two-center study was to develop a radiomics model with all-relevant imaging features from multiphasic computed tomography...

European Radiology

5 months ago