mri

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

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

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

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

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

5 months ago

Quality assurance for automatically generated contours with additional deep learning

This study explores the importance of quality assurance when deploying an automatic segmentation model. The authors of this study built a deep-learning model...

Insights into Imaging

6 months ago

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 periodically rotated overlapping parallel line with enhanced...

European Radiology

6 months ago

Tasks for AI in prostate MRI

The authors of this narrative review aimed to introduce quality metrics for emerging artificial intelligence (AI) papers, such as the Checklist for Artificial...

European Radiology Experimental

6 months ago

Prediction of lipomatous soft tissue malignancy on MRI

This study, which included a cohort of 145 patients affected by lipomatous soft tissue tumours, aimed to compare the performances of MRI radiomic machine...

European Radiology Experimental

8 months ago

Machine learning–based radiomics classifies parotid tumors using morphological MRI

This comparative study aimed to evaluate the effectiveness of machine learning models based on morphological MRI radiomics in the classification of parotid...

European Radiology

10 months ago