Endometrial cancer (EC) has the highest rate of malignancy in women in the entire world, including China, which has the largest population. Accurately staging...
Multiple automated methods for segmentation of multiple sclerosis (MS) lesions have been developed over the past years, and the use of artificial neural...
This preliminary study aimed to differentiate malignant from benign enhancing foci on breast MRI using radiomic signature. Forty-five patients were included...
In this study, the authors developed a deep feature fusion model (DFFM) in order to segment postoperative gliomas on CT images, which were guided by...
The purpose of this study was to create a radiomics approach based on multiparametric MRI (mpMRI) features that were extracted from an auto-fixed volume of...
The authors of this study aimed to assess the performance of a convolutional neural network (CNN) algorithm to register cross-sectional liver imaging series...
This study integrated the clinical data and radiomics signature generated by a support vector machine to establish a radiomics nomogram for prediction of...
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.