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

OBJECTIVES: Diagnostic accuracy of artificial intelligence (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 in-image annotations of the dehiscent visceral pleura fo...

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Detalles Bibliográficos
Autores principales: Rueckel, Johannes, Huemmer, Christian, Fieselmann, Andreas, Ghesu, Florin-Cristian, Mansoor, Awais, Schachtner, Balthasar, Wesp, Philipp, Trappmann, Lena, Munawwar, Basel, Ricke, Jens, Ingrisch, Michael, Sabel, Bastian O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452588/
https://www.ncbi.nlm.nih.gov/pubmed/33774722
http://dx.doi.org/10.1007/s00330-021-07833-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452588/
https://www.ncbi.nlm.nih.gov/pubmed/33774722
http://dx.doi.org/10.1007/s00330-021-07833-w

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