deep learning

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

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

Optimal matrix size of chest radiographs for computer-aided detection on lung nodule or mass with deep learning

In this study, the authors retrospectively collected 2,088 abnormal and 352 normal chest radiographs from two institutions in order to investigate the optimal...

European Radiology

3 years ago

Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer

The purpose of this retrospective study was to develop and evaluate the performance of U-Net to determine whether U-Net-based deep learning could accurately...

European Radiology

3 years ago

Deep learning: definition and perspectives for thoracic imaging

The authors of this review aimed to provide definitions for understanding the methods of machine learning, deep learning, and convolutional neural networks...

European Radiology

3 years ago

Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT

The authors of this study aimed to determine the diagnostic performance of a deep learning algorithm for the automated detection of small 18F-FDG-avid...

European Radiology

3 years ago

Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound

The aim of this study was to establish and validate an artificial intelligence-based radiomics strategy in order to predict personalized responses to...

European Radiology

3 years ago

Deep learning workflow in radiology: how to get started

In the past decade, deep learning architectures, which essentially consist of neural networks with numerous layers, have emerged as a dominant class of...

An Tang

3 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

3 years 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

3 years ago