|Publisher DOI:||10.1109/ISBI48211.2021.9434022||Title:||Landmark constellation models for central venous catheter malposition detection||Language:||English||Authors:||Sirazitdinov, Ilyas
Baltruschat, Ivo M.
Dylov, Dmitry V.
|Keywords:||Central venous catheter;Constellation model;Landmark detection;Malposition detection;X-ray||Issue Date:||13-Apr-2021||Source:||IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021)||Abstract (english):||
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.
|Conference:||IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021)||URI:||http://hdl.handle.net/11420/9726||ISBN:||978-166541246-9||Institute:||Biomedizinische Bildgebung E-5||Document Type:||Chapter/Article (Proceedings)|
|Appears in Collections:||Publications without fulltext|
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