mri

Reasons to do AI with Friends: The one where we classify breast cancer with MRI

“This was just awesome!” “Fantastic!” “Thank you for this great session!” These were only a few of the feedback messages...

ESR

3 years ago

Combining DWI radiomics features with transurethral resection promotes the differentiation between muscle-invasive bladder cancer and non-muscle-invasive bladder cancer

The purpose of this retrospective study was to investigate the value of radiomics features from diffusion-weighted imaging (DWI) in differentiating...

European Radiology

3 years ago

Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer

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...

ESR

3 years ago

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

The authors of this study aimed to assess the performance of a convolutional neural network (CNN) algorithm to register cross-sectional liver imaging series...

European Radiology Experimental

3 years ago

MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma

This study integrated the clinical data and radiomics signature generated by a support vector machine to establish a radiomics nomogram for prediction of...

European Radiology

3 years ago

Why radiomics research does not translate to clinical practice: evaluation of literature using RQS and TRIPOD

Over the last few years, the number of studies published using quantitative imaging biomarkers to classify or predict pathologies has steadily increased. As...

Daniel Pinto dos Santos

4 years ago

Deep learning to differentiate parkinsonian disorders separately using single midsagittal MR imaging

In an attempt to determine whether deep learning with the convolutional neural networks (CNN) can be used for identifying parkinsonian disorder on MRI, the...

European Radiology

4 years ago

Machine learning classifiers vs. Experienced radiologists: Predicting Gleason pattern 4 prostate cancer

The authors of this study recognized the potential of multiparametric positron emission tomography/magnetic resonance imaging (mpPET/MRI) for detecting and...

European Radiology

4 years ago

Automatic segmentation and classification of breast lesions through identification of informative multiparametric PET/MRI features

The authors of this study recognized the potential of multiparametric positron emission tomography/magnetic resonance imaging (mpPET/MRI) for detecting and...

European Radiology Experimental

4 years ago

Using radiomics for the preoperative estimation of pathological grade in bladder cancer tumors

The goal of this study was to develop and authenticate an MRI-based radiomics strategy for the preoperative estimation of pathological grade in bladder cancer...

European Radiology

4 years ago