Using Artificial Intelligence for Automatic Segmentation of CT Lung Images in Acute Respiratory Distress Syndrome

Using Artificial Intelligence for Automatic Segmentation of CT Lung Images in Acute Respiratory Distress Syndrome

Knowledge of gas volume, tissue mass and recruitability measured by the quantitative CT scan analysis (CT-qa) is important when setting the mechanical ventilation in acute respiratory distress syndrome (ARDS). Yet, the manual segmentation of the lung requires a considerable workload. Our goal was to...

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Bibliographic Details
Main Authors: Peter Herrmann, Mattia Busana, Massimo Cressoni, Joachim Lotz, Onnen Moerer, Leif Saager, Konrad Meissner, Michael Quintel, Luciano Gattinoni
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Physiology
Subjects:
ARDS
fully automatic lung segmentation
deep learning
U-Net
LabVIEW
DeepLTK
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2021.676118/full

Internet

https://www.frontiersin.org/articles/10.3389/fphys.2021.676118/full

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