Diagnostic and interventional imaging
Mar 28, 2019
PURPOSE: The purpose of this study was to build and evaluate a high-performance algorithm to detect and characterize the presence of a meniscus tear on magnetic resonance imaging examination (MRI) of the knee.
Diagnostic and interventional imaging
Mar 27, 2019
PURPOSE: This work presents our contribution to one of the data challenges organized by the French Radiology Society during the Journées Francophones de Radiologie. This challenge consisted in segmenting the kidney cortex from coronal computed tomogr...
Diagnostic and interventional imaging
Mar 27, 2019
PURPOSE: The purpose of this study was to create an algorithm that simultaneously detects and characterizes (benign vs. malignant) focal liver lesion (FLL) using deep learning.
Diagnostic and interventional imaging
Mar 26, 2019
PURPOSE: The purpose of this study was to assess the potential of a deep learning model to discriminate between benign and malignant breast lesions using magnetic resonance imaging (MRI) and characterize different histological subtypes of breast lesi...
Diagnostic and interventional imaging
Mar 23, 2019
PURPOSE: This work presents our contribution to a data challenge organized by the French Radiology Society during the Journées Francophones de Radiologie in October 2018. This challenge consisted in classifying MR images of the knee with respect to t...
Diagnostic and interventional imaging
Mar 15, 2019
PURPOSE: The goal of this data challenge was to create a structured dynamic with the following objectives: (1) teach radiologists the new rules of General Data Protection Regulation (GDPR), while building a large multicentric prospective database of ...
Diagnostic and interventional imaging
Feb 25, 2019
PURPOSE: The purpose of this study was to evaluate the performance of a deep learning algorithm in detecting abnormalities of thyroid cartilage from computed tomography (CT) examination.
Diagnostic and interventional imaging
Nov 27, 2018
INTRODUCTION: The purpose of this study was to develop a convolutional neural network (CNN) to determine the extent of over-scanning in the Z-direction associated with lung computed tomography (CT) examinations.
Diagnostic and interventional imaging
Nov 22, 2018
The rapid development of information technology and data processing capabilities has led to the creation of new tools known as artificial intelligence (AI). Medical applications of AI are emerging, and the French radiology community felt it was there...
PURPOSE: To evaluate the feasibility and reproducibility of artificial intelligence software (Smartplanes) to automatically identify the transthalamic plane from 3D ultrasound volumes and to measure the biparietal diameter (BPD) and head circumferenc...