Over a decade in the making, the novel concept of radiomics has been silently brewing, promising to reshape the landscape of personalised and precision...
This study evaluates deep learning (DL) algorithms that are playing an increasingly important role in automatic medical image analysis. The DL algorithm used...
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....
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....
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...
The authors of this narrative review aimed to introduce quality metrics for emerging artificial intelligence (AI) papers, such as the Checklist for Artificial...
The aim of this study was to provide an updated systematic review of radiomics in osteosarcoma, utilizing various databases such as PubMed, Embase, China...
Because the early detection of dysthyroid optic neuropathy (DON) is of the utmost importance for clinical decision-making, the authors of this study aimed to...
This retrospective study evaluated deep learning algorithms for the detection of automatic rib fracture on thoracic CT scans. The authors also aimed to...
In radiomics, the main goal is to extract quantitative features from medical data to train a predictive model using machine learning techniques. Contrary to...
When the Radiomics Quality Score (RQS) was presented to the scientific community back in 2017, its authors aimed to introduce a tool for a rapid and effective...
This study, which included a cohort of 145 patients affected by lipomatous soft tissue tumours, aimed to compare the performances of MRI radiomic machine...
Dr. Rizwan Aslam, of the University of California, San Francisco (UCSF), presented an abstract at RSNA in 2008 which showed that it was possible to screen for...
In this study, the authors evaluated the diagnostic capability, image quality, and radiation dose of abdominal ultra-low-dose CT (ULDCT) with deep learning...
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.
