Sirazitdinov, IlyasIlyasSirazitdinovLenga, MatthiasMatthiasLengaBaltruschat, Ivo M.Ivo M.BaltruschatDylov, Dmitry V.Dmitry V.DylovSaalbach, AxelAxelSaalbach2021-06-112021-06-112021-04-13IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021)http://hdl.handle.net/11420/9726The 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.enCentral venous catheterConstellation modelLandmark detectionMalposition detectionX-rayConference Paper10.1109/ISBI48211.2021.9434022Other