Articles

Evaluating the impact of a novel denoising algorithm on image quality in dual-energy abdominal CT of obese patients

In the ever-evolving landscape of radiology, the quest for enhanced image quality and reduced noise, particularly in obese patients, remains an enduring...

Fides Regina Schwartz

3 days ago

Unlocking the Potential of Radiomics: Ongoing Challenges Are Revolving Around Methodology and Reproducibility

Over a decade in the making, the novel concept of radiomics has been silently brewing, promising to reshape the landscape of personalised and precision...

Hyun Soo Ko

1 week ago

Evaluation of techniques to improve a deep learning algorithm for the automatic detection of intracranial haemorrhage on CT head imaging

This study evaluates deep learning (DL) algorithms that are playing an increasingly important role in automatic medical image analysis. The DL algorithm used...

European Radiology Experimental

2 weeks ago

Multi-channel deep learning model diagnoses the cause of LVH

A new study sees the development of a fully automatic framework for the diagnosis of the cause of left ventricular hypertrophy (LVH) via cardiac cine images....

Insights into Imaging

3 weeks ago

Evaluating a deep learning software for lung parenchyma characterization in COVID-19 pneumonia

The aim of this study was to evaluate the performance of the LungQuant system, which is a deep learning-based software for quantitative analysis of chest CT....

European Radiology Experimental

1 month ago

Robustness of pulmonary nodule radiomic features on CT as a function of varying radiation dose levels

The aim of this study was to present an in vivo stability analysis of radiomic features for pulmonary nodules against varying radiation dose levels. The...

European Radiology

1 month ago

Robustness of pulmonary nodule radiomic features on CT as a function of varying radiation dose levels

Reproducibility of a combined AI and optimal-surface graph-cut method to automate bronchial parameter extraction

The authors of this study evaluated the reproducibility of a deep learning and optimal-surface graph-cut method to automatically segment the airway lumen and...

European Radiology

2 months ago

Reproducibility of a combined AI and optimal-surface graph-cut method to automate bronchial parameter extraction

Quo vadis Radiomics? Bibliometric analysis of 10-year Radiomics journey

This study conducted a bibliometric analysis of radiomics ten years after the first work became available in March 2012. Throughout the analysis, the authors...

European Radiology

2 months ago

Quo vadis Radiomics? Bibliometric analysis of 10-year Radiomics journey

A novel AI model to distinguish benign from malignant ovarian tumors

The authors of this study developed a CT-based artificial intelligence model with the ability to differentiate between benign and malignant ovarian tumors,...

Insights into Imaging

2 months ago

A novel AI model to distinguish benign from malignant ovarian tumors

Aging-related volume changes in the brain and cerebrospinal fluid using AI-automated segmentation

Deep learning methods to quantitatively assess disease-specific brain atrophy from CT and MRI images are rapidly gaining popularity, and a new era of clinical...

Shigeki Yamada

2 months ago

Aging-related volume changes in the brain and cerebrospinal fluid using AI-automated segmentation

Structured reporting using an intelligent dialogue system based on speech recognition and NLP

Although structured reporting (SR) is recommended in the field of radiology compared to free-text reporting (FTR), the use of SR still experiences obstacles...

Insights into Imaging

2 months ago

Structured reporting using an intelligent dialogue system based on speech recognition and NLP

Intelligent noninvasive meningioma grading using deep learning

The purpose of this study was to establish a robust interpretable deep learning (DL) model for the automatic noninvasive grading of meningiomas along with...

European Radiology

3 months ago

Intelligent noninvasive meningioma grading using deep learning

AI-aided software for detecting visible clinically significant prostate cancer on mpMRI

This study seeks to determine if artificial intelligence (AI)-based software can improve radiologists’ performance when detecting clinically significant...

Insights into Imaging

3 months ago

AI-aided software for detecting visible clinically significant prostate cancer on mpMRI

Using a multi-decoder water-fat separation neural network for liver PDFF estimation

The authors of this study proposed a multi-task U-Net-based architecture to jointly estimate water-only and fat-only images. This approach allowed for the...

European Radiology

3 months ago

Using a multi-decoder water-fat separation neural network for liver PDFF estimation

Hepatic steatosis increases liver volume

Our recent research published in European Radiology aimed to evaluate the impact of hepatic steatosis (HS) on liver volume by conducting a retrospective...

Seung Soo Lee

3 months ago

Hepatic steatosis increases liver volume

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Welcome to the blog on Artificial Intelligence of the European Society of Radiology

This blog aims at bringing educational and critical perspectives on AI to readers. It should help imaging professionals to learn and keep up to date with the technologies being developed in this rapidly evolving field.

Welcome to the blog on Artificial Intelligence of the European Society of Radiology

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