tomography

Creating a training set for AI from initial segmentations of airways

An important challenge in the use of artificial intelligence (AI) for medical image segmentation tasks is the lack of high-quality, scan protocol-specific...

Ivan Dudurych

4 weeks ago

Machine learning automatically detects COVID-19 using chest CTs in a large multicenter cohort

This retrospective, multi-institutional study investigated machine learning classifiers and interpretable models using chest CT for the detection of COVID-19...

European Radiology

6 months ago

A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients

The authors of this study analyzed and compared the imaging workflow, radiation dose, and image quality for 127 adult COVID-19 patients who were examined...

European Radiology

11 months ago

Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19

In this study, the authors aimed to develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with...

European Radiology

12 months ago

Emphysema quantification using low-dose computed tomography with deep learning-based kernel conversion comparison

This study used a sample of 131 participants who underwent low-dose computed tomography (LDCT) and standard-dose computed tomography (SDCT) to determine the...

European Radiology

2 years ago

Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography

In this study, the authors proposed a deep learning method for the detection and quantification of pneumothorax in heterogeneous routine clinical data, which...

European Radiology Experimental

2 years ago

Development and validation of machine learning prediction model based on computed tomography angiography–derived hemodynamics for rupture status of intracranial aneurysms: a Chinese multicenter study

Decisions regarding the optimal management of unruptured intracranial aneurysms (UIAs) depend on a comprehensive comparison of the risks between aneurysm...

Guo Zhong Chen

2 years ago

Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach

The aim of this study was to evaluate whether machine learning algorithms allow for the prediction of Child-Pugh classification on clinical multiphase...

European Radiology Experimental

2 years ago

Radiomics allows for detection of benign and malignant histopathology in patients with metastatic testicular germ cell tumors prior to post-chemotherapy retroperitoneal Iymph node dissection

Among solid tumors, testicular germ cell tumors (TGCT) are the most common entity in men below the age of 40, and they are very likely to metastasize. The...

Bettina Baeßler

2 years 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 years ago