Publications

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

5 days ago

Dual-energy CT–based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer

In this study, the authors aimed to build a dual-energy CT (DECT)-based deep learning radiomics nomogram that could be used for lymph node metastasis...

European Radiology

2 weeks 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 weeks ago

Marginal radiomics features as imaging biomarkers for pathological invasion in lung adenocarcinoma

This study identified 236 patients from two cohorts who underwent surgery for ground-glass nodules (GGNs). The novel marginal features described, when...

European Radiology

4 weeks 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

1 month 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

1 month ago

Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification

The authors of this study evaluated the impact of utilizing digital breast tomosynthesis (DBT) and/or full-field digital mammography (FFDM), and different...

European Radiology

2 months ago

Radiogenomics of lower-grade gliomas: machine learning–based MRI texture analysis for predicting 1p/19q codeletion status

In this work, we aimed to evaluate the potential value of the machine learning (ML)–based MRI texture analysis for predicting 1p/19q codeletion status of...

Burak Kocak

2 months ago

Reading recommendation – Reasons to do AI with Friends

The literature below has been hand-selected as recommended reading to complement the topics covered during Season 2 of ‘AI-Use Cases: Reasons to do AI...

ESR

2 months ago

Patients’ views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire

In this study, the authors aimed to develop and validate a patient questionnaire on the patients’ view on the implementation of artificial intelligence...

European Radiology

2 months ago