Automated Precision Localization of Peripherally Inserted Central Catheter Tip through Model-Agnostic Multi-Stage Networks. (arXiv:2206.06730v1 [eess.IV])

Peripherally inserted central catheters (PICCs) have been widely used as one
of the representative central venous lines (CVCs) due to their long-term
intravascular access with low infectivity. However, PICCs have a fatal drawback
of a high frequency of tip mispositions, increasing the risk of puncture,
embolism, and complications such as cardiac arrhythmias. To automatically and
precisely detect it, various attempts have been made by using the latest deep
learning (DL) technologies. However, even with these approaches, it is still
practically …

arxiv localization model-agnostic networks precision stage