Automated Detection and Type Classification of Central Venous Catheters in Chest X-Rays

07/02/2019
by   Vaishnavi Subramanian, et al.
0

Central venous catheters (CVCs) are commonly used in critical care settings for monitoring body functions and administering medications. They are often described in radiology reports by referring to their presence, identity and placement. In this paper, we address the problem of automatic detection of their presence and identity through automated segmentation using deep learning networks and classification based on their intersection with previously learned shape priors from clinician annotations of CVCs. The results not only outperform existing methods of catheter detection achieving 85.2 91.6 catheter types on a large dataset of over 10,000 chest X-rays, presenting a robust and practical solution to this problem.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset