Abstract
Purpose
To present an automated method for detecting endotracheal (ET) tubes and marking their tips in portable chest radiography (CXR) for intensive care units (ICUs).
Methods
In this method, the lung region is first estimated and then the spine is detected between the right lung and the left lung. Because medical tubes are inserted into the body through the throat, the region of interest (ROI) is obtained across the spine. A seed point is determined in the cervical region of the ROI, and then the line path is selected from the seed point. In order to detect ET tubes, the ICU CXR image is preprocessed by contrast-limited adaptive histogram equalization. Then, a feature-based threshold method is applied to the line path to determine the tip location. A comparison to the method by use of Hough transform is also presented. The distance (error) between the detected locations and the locations annotated by a radiologist is used to evaluate the detection precision for the tip location.
Results
The proposed method is evaluated using 44 images with ET tubes and 43 images without ET tubes. The discriminant performance for detecting the existence of ET tubes in this study was 95 %, and the average of detection error for the tip location was approximately 2.5 mm.
Conclusions
The proposed method could be useful for detecting malpositioned ET tubes in ICU CXRs.
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Funding
This work was supported by the National Science Foundation of China (NSFC) 81101116, the Foundation of Hujiang (C14002), and the National Sciences Foundation of Shanghai (13ZR1410400).
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
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Informed consent was obtained from all individual participants included in the study.
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Chen, S., Zhang, M., Yao, L. et al. Endotracheal tubes positioning detection in adult portable chest radiography for intensive care unit. Int J CARS 11, 2049–2057 (2016). https://doi.org/10.1007/s11548-016-1430-3
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DOI: https://doi.org/10.1007/s11548-016-1430-3