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Articles

Covid-19 early detection: Neural Networks vs. Radiologists

The COVID-19 pandemic not only made an impact on the discipline of radiology as a whole but also on how we use specific tools in its detection. This was...

Insights into Imaging

Covid-19 early detection: Neural Networks vs. Radiologists

Articles

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

Deep learning image reconstruction improves DECT image quality

Articles

Automated vetting of radiology referrals: exploring NLP and ML approaches

As computed tomography (CT) sees an increase in utilization, inappropriate imaging has been seen as a significant concern; however, manual justification...

Insights into Imaging

Automated vetting of radiology referrals: exploring NLP and ML approaches

Articles

T2-weighted MRI-based radiomics discriminati between benign and borderline epithelial ovarian tumors

The authors of this study investigated whether radiomics based on T2-weighted MRI was able to discriminate between benign and borderline epithelial ovarian...

Insights into Imaging

T2-weighted MRI-based radiomics discriminati between benign and borderline epithelial ovarian tumors

Articles

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

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

Covid-19 early detection: Neural Networks vs. Radiologists

The COVID-19 pandemic not only made an impact on the discipline of radiology as a whole but also...

Insights into Imaging

12 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...

European Radiology

1 week ago

Automated vetting of radiology referrals: exploring NLP and ML approaches

As computed tomography (CT) sees an increase in utilization, inappropriate imaging has been seen...

Insights into Imaging

2 weeks ago

T2-weighted MRI-based radiomics discriminati between benign and borderline epithelial ovarian tumors

The authors of this study investigated whether radiomics based on T2-weighted MRI was able to...

Insights into Imaging

3 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...

European Radiology

4 weeks ago

Enhanced CT-based radiomics predicts pathological complete response for advanced adenocarcinoma

This study shows that the combination of CT imaging and clinical factors pre-neoadjuvant...

Insights into Imaging

1 month ago

Enhanced CT-based radiomics predicts pathological complete response for advanced adenocarcinoma

AI for prostate MRI: open datasets, available applications, and grand challenges

This narrative review provides an overview of the current state-of-the-art artificial intelligence...

European Radiology Experimental

1 month ago

AI for prostate MRI: open datasets, available applications, and grand challenges

Quality assurance for automatically generated contours with additional deep learning

This study explores the importance of quality assurance when deploying an automatic segmentation...

Insights into Imaging

2 months ago

Quality assurance for automatically generated contours with additional deep learning

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...

European Radiology

2 months ago

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

Tasks for AI in prostate MRI

The authors of this narrative review aimed to introduce quality metrics for emerging artificial...

European Radiology Experimental

2 months ago

Utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics

The aim of this study was to provide an updated systematic review of radiomics in osteosarcoma,...

Insights into Imaging

2 months ago

Utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics

Detecting dysthyroid optic neropathy using radiomics analysis of the optic nerve

Because the early detection of dysthyroid optic neuropathy (DON) is of the utmost importance for...

Insights into Imaging

3 months ago

Detecting dysthyroid optic neropathy using radiomics analysis of the optic nerve

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...

European Radiology

3 months ago

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

The effect of preprocessing filters on predictive performance in radiomics

In radiomics, the main goal is to extract quantitative features from medical data to train a...

Aydin Demircioğlu

3 months ago

The effect of preprocessing filters on predictive performance in radiomics

EuSoMII Radiomics Auditing Group Initiative: Review of RQS applications

When the Radiomics Quality Score (RQS) was presented to the scientific community back in 2017, its...

Arnaldo Stanzione

3 months ago

EuSoMII Radiomics Auditing Group Initiative: Review of RQS applications

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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