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Landmark constellation models for central venous catheter malposition detection
Publikationstyp
Conference Paper
Date Issued
2021-04-13
Sprache
English
Institut
TORE-URI
Start Page
1132
End Page
1136
Article Number
9434022
Citation
IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021)
Contribution to Conference
Publisher DOI
Scopus ID
The placement of a central venous catheter (CVC) for venous access is a common clinical routine. Nonetheless, various clinical studies report that CVC insertions are unsuccessful in up to 20% of all cases. Among other, typical complications include the incidence of a pneumothorax, hemothorax, arterial puncture, venous air embolism, arrhythmias or catheter knotting. In order to detect the CVC tip in chest X-ray (CXR) images, and to evaluate the catheter placement, we propose a HRNet-based key point detection approach in combination with a probabilistic constellation model. In a cross-validation study, we show that our approach not only enables the exact localization of the CVC tip, but also of relevant anatomical landmarks. Moreover, the probabilistic model provides a likelihood score for tip position which allows us to identify malpositioned CVCs.
Subjects
Central venous catheter
Constellation model
Landmark detection
Malposition detection
X-ray