Image augmentation and automated measurement of endotracheal-tube-to-carina distance on chest radiographs in intensive care unit using a deep learning model with external validation

Image augmentation and automated measurement of endotracheal-tube-to-carina distance on chest radiographs in intensive care unit using a deep learning model with external validation

Abstract Background Chest radiographs are routinely performed in intensive care unit (ICU) to confirm the correct position of an endotracheal tube (ETT) relative to the carina. However, their interpretation is often challenging and requires substantial time and expertise. The aim of this study was t...

Full description

Bibliographic Details
Main Authors: Matthieu Oliver, Amélie Renou, Nicolas Allou, Lucas Moscatelli, Cyril Ferdynus, Jerôme Allyn
Format: Article
Language:English
Published: BMC 2023-01-01
Series:Critical Care
Subjects:
Intensive care unit
Chest radiograph
RetinaNet
Deep learning
Image processing
Online Access:https://doi.org/10.1186/s13054-023-04320-0

Internet

https://doi.org/10.1186/s13054-023-04320-0

Similar Items