mri

MRI radiomics features predict immuno-oncological characteristics of hepatocellular carcinoma

Advanced hepatocellular carcinoma (HCC) carries a dismal prognosis. For a decade, sorafenib, a multi-kinase inhibitor, was the only approved systemic therapy...

Stefanie Hectors

3 weeks ago

Radiomics based on brain MRI is expected to be a useful tool for early identification and prediction of WMH progression

As a research hotspot in recent years, radiomics provides a new perspective for image diagnosis or evaluation by mining a large number of non-traditional...

Yuyun Xu

1 month ago

Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis

The goal of this study was to assess the diagnostic accuracy of machine learning in the prediction of isocitrate dehydrogenase (IDH) mutations, particularly...

European Radiology

2 months ago

Deep learning for the determination of myometrial invasion depth and automatic lesion identification in endometrial cancer MR imaging

Endometrial cancer (EC) has the highest rate of malignancy in women in the entire world, including China, which has the largest population. Accurately staging...

He Zhang

3 months ago

Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis

Multiple automated methods for segmentation of multiple sclerosis (MS) lesions have been developed over the past years, and the use of artificial neural...

Philipp Kickingereder

7 months ago

Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas?

In this study, the authors aimed to improve the prediction of patients’ prognosis of myxoid/round cell liposarcomas (MRC-LPS) using a radiomics...

European Radiology

8 months ago

A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI

This preliminary study aimed to differentiate malignant from benign enhancing foci on breast MRI using radiomic signature. Forty-five patients were included...

European Radiology Experimental

8 months ago

Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs

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...

European Radiology

8 months ago

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

9 months 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

10 months ago