mri

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

2 months ago

The role of generative adversarial networks in brain MRI

Magnetic Resonance Imaging (MRI) is a widely used medical imaging technology that is non-intrusive and considered safe for humans and can generate different...

Hazrat Ali

3 months ago

Deep learning detection of ACL tear on knee MRI

The purpose of this study was to develop a deep-learning algorithm for tear detection in the anterior cruciate ligament (ACL), subsequently comparing its...

European Radiology

5 months ago

Single-center versus multi-center biparametric MRI radiomics approach

In this study, the authors’ aim was to investigate a previously developed radiomics-based biparametric magnetic resonance imaging (bpMRI) approach used...

Insights into Imaging

8 months ago

Radiomics in the prediction of disease-free survival in early-stage squamous cervical cancer

The authors of this study conducted multiparametric magnetic resonance imaging (MRI)-derived radiomics based on multi-scale tumor region in order to predict...

European Radiology

9 months ago

Saliency-based 3D convolutional neural network for categorising common focal liver lesions on multisequence MRI

We investigated a saliency-based 3D convolutional neural network (CNN) to classify seven categories of common focal liver lesions and validated the model...

Zheng-Han Yang

12 months ago

How can we combat multicenter variability in MR radiomics? Validation of a correction procedure

In this study, the authors extended the ComBat approach to provide a harmonization procedure that is applicable to any radiomic feature. They achieve this by...

European Radiology

2 years ago

Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment

We use a previously validated artificial neural network to evaluate its performance in a much larger, subsequent, consecutive cohort. In the community, there...

David Bonekamp

2 years ago

Radiologists with MRI-based radiomics aids to predict the pelvic lymph node metastasis in endometrial cancer: a multicenter study

The purpose of this study, performed between January 2014 and May 2019 across five different centers, was to construct an MRI radiomics model and help...

European Radiology

2 years ago

Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas

This study aimed to evaluate whether radiomics from magnetic resonance imaging (MRI) would allow for the prediction of the overall survival in patients with...

European Radiology

2 years ago