Publisher DOI: 10.1109/ISBI48211.2021.9434022
Title: Landmark constellation models for central venous catheter malposition detection
Language: English
Authors: Sirazitdinov, Ilyas 
Lenga, Matthias 
Baltruschat, Ivo M.  
Dylov, Dmitry V. 
Saalbach, Axel 
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)
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