deep learning

Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment

We use a previously validated artificial neural network to evaluate its performance in a much larger, subsequent, consecutive cohort. In the community, there...

David Bonekamp

9 hours ago

From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans

In this retrospective study, the authors aimed to develop a fully automated artificial intelligence (AI) system to quantitatively assess the severity and...

European Radiology

2 months ago

Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration

The purpose of this study was to evaluate the calibration of a deep learning (DL) model in a diagnostic cohort, as well as to improve the model’s...

European Radiology

2 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

3 months 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

4 months 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

6 months 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

7 months 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

8 months 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

8 months 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

9 months ago