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) 
ISBN: 978-166541246-9
Institute: Biomedizinische Bildgebung E-5 
Document Type: Chapter/Article (Proceedings)
Appears in Collections:Publications without fulltext

Show full item record

Page view(s)

checked on Jun 19, 2021

Google ScholarTM


Add Files to Item

Note about this record

Cite this record


Items in TORE are protected by copyright, with all rights reserved, unless otherwise indicated.