Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography

Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography

Abstract Background Automatically detecting and quantifying pneumothorax on chest computed tomography (CT) may impact clinical decision-making. Machine learning methods published so far struggle with the heterogeneity of technical parameters and the presence of additional pathologies, highlighting t...

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Bibliographic Details
Main Authors: Sebastian Röhrich, Thomas Schlegl, Constanze Bardach, Helmut Prosch, Georg Langs
Format: Article
Language:English
Published: SpringerOpen 2020-04-01
Series:European Radiology Experimental
Subjects:
Deep learning
Pneumothorax
Thorax
Tomography (x-ray computed)
Triage
Online Access:http://link.springer.com/article/10.1186/s41747-020-00152-7

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http://link.springer.com/article/10.1186/s41747-020-00152-7

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