x-ray computed tomography

Can radiomics signatures predict tumor reponse of patients treated with chemotherapy and targeted therapy?

The authors of this retrospective study had the goal of evaluating the effectiveness of radiomics signatures in order to predict the tumor response of...

European Radiology

1 month ago

Can machine learning predict the WHO/ISUP nuclear grade of clear cell renal cell carcinomas?

In this retrospective study, the authors investigated if radiomics features extracted from nephrographic-phase (NP) CT images combined with...

Insights into Imaging

2 months ago

Radiomic nomogram predicts pathology invasiveness

The purpose of this retrospective diagnostic study was to develop and validate a preoperative CT-based nomogram combined with radiomic and...

European Radiology

4 months ago

Proposing a deep learning-based method for improving the diagnostic certainty of pulmonary nodules in CT scan of chest

The aim of this study was to compare the performance of a deep learning (DL)-based method used for diagnosing pulmonary nodules compared with the diagnostic...

European Radiology

8 months ago

Differential diagnosis of benign and malignant vertebral fracture on CT using deep learning

The purpose of this study was to evaluate the performance of deep learning using ResNet50 in the differentiation of benign and malignant vertebral fracture on...

European Radiology

9 months ago

Practice makes perfect: Using AR to simulate CT guided procedures

As a junior radiology trainee, when I was not in the reporting room or on the wards doing portable ultrasounds, I found learning CT procedures a daunting task...

Dimitri Amiras

10 months ago

Deep learning–based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC

Of late, deep learning-based algorithms have been successfully applied to various medical imaging modalities, ranging from chest radiographs to head CT scans....

So Yeon Kim

12 months ago

Development and multicenter validation of a CT-based radiomics signature for predicting severe COVID-19 pneumonia

The authors of this study aimed to develop and validate a radiomics nomogram for the prompt prediction of severe COVID-19 pneumonia. This was done through the...

European Radiology

1 year ago

Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks

In this study, the authors explored the application of deep learning in patients with primary osteoporosis. Furthermore, they aimed to develop a fully...

European Radiology

1 year ago

Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique

The authors of this study aimed to evaluate the image quality of low iodine concentration, dual-energy CT (DECT) combined with a deep learning-based noise...

European Radiology

1 year ago