mri

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

Improved characterization of sub-centimeter enhancing breast masses on MRI with radiomics and machine learning in BRCA mutation carriers

This retrospective study aimed to investigate whether radiomics features extracted from MRI of BRCA-positive patients with sub-centimeter breast masses can be...

European Radiology

2 years ago

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

2 years 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

2 years 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

3 years 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 years 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

3 years 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

3 years 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

3 years 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

3 years ago