Impact of confounding thoracic tubes and pleural dehiscence extent on artificial intelligence pneumothorax detection in chest radiographs

J Rueckel, L Trappmann, B Schachtner… - … Radiology, 2020 - journals.lww.com
… (AI) pneumothorax (PTX) detection in chest radiographs (CXRs) do not sufficiently consider
the influence of PTX size and confounding effects caused by thoracic tubes (TTs). Therefore, …

Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in …

J Rueckel, C Huemmer, A Fieselmann, FC Ghesu… - … radiology, 2021 - Springer
… (AI) pneumothorax (PTX) detection in chest radiographs (CXR) is limited by the noisy
annotation quality of public training data and confounding thoracic tubes (TT). We hypothesize that …

Endotracheal tube position assessment on chest radiographs using deep learning

P Lakhani, A Flanders, R Gorniak - Radiology: Artificial Intelligence, 2020 - pubs.rsna.org
… of 0.99 for detecting the presence of ETT at chest radiography (16,… to determine whether a
different approach using deep learning … tubes, be used to flag reading worklists, and expedite …

Identification and localization of endotracheal tube on chest radiographs using a cascaded convolutional neural network approach

S Kara, JY Akers, PD Chang - Journal of Digital Imaging, 2021 - Springer
… In recent years, CNN-based techniques have been recognized as state-of-the-art on various
medical imaging tasks related to chest radiograph analysis, including pneumonia detection […

Deep learning systems for pneumothorax detection on chest radiographs: a multicenter external validation study

YL Thian, D Ng, JTPD Hallinan, P Jagmohan… - Radiology: Artificial …, 2021 - pubs.rsna.org
… Model performance was not different when a chest tube was present or absent on the
radiographs (AUC, 0.95 [95% CI: 0.92, 0.97] vs AUC, 0.94 [95% CI: 0.92, 0.05]; P > .99). …

Chest radiographs and machine learning–Past, present and future

CM Jones, QD Buchlak… - Journal of Medical …, 2021 - Wiley Online Library
… 44 and lead to failure to detect high-risk pathologies. The archetypal example is that of
detecting pneumothoraces without chest drains. As chest drains are visually obvious and inserted …

Deep learning for detecting pneumothorax on chest radiographs after needle biopsy: clinical implementation

W Hong, EJ Hwang, JH Lee, J Park, JM Goo, CM Park - Radiology, 2022 - pubs.rsna.org
detection on chest radiographs was implemented in an institution in February 2020. This
retrospective cohort study consecutively included chest radiographs … the radiograph reader and …

Deep-learning-based diagnosis of bedside chest X-ray in intensive care and emergency medicine

SM Niehues, LC Adams, RA Gaudin… - … radiology, 2021 - journals.lww.com
… However, radiographs with a thoracic drain showed a … to expert radiologists for the
detection of different medical … for the detection of central venous catheters, thoracic drains, …

Deep Learning–Based Localization and Detection of Malpositioned Nasogastric Tubes on Portable Supine Chest X-Rays in Intensive Care and Emergency Medicine …

CH Wang, T Hwang, YS Huang, J Tay, CY Wu… - Journal of Imaging …, 2024 - Springer
… Malposition of a nasogastric tube (NGT) can lead to severe complications. We aimed to …
detection (CAD) system to localize NGTs and detect NGT malposition on portable chest X-rays (…

Blunt thoracic trauma: role of chest radiography and comparison with CT—findings and literature review

K Polireddy, C Hoff, NP Kinger, A Tran, K Maddu - Emergency Radiology, 2022 - Springer
… d Follow-up CXR post TEVAR with stent placement (arrows) and chest tube drainage of the
… 98.5% in detecting rib fractures, respectively [49]. Chest radiographs can detect multilevel …