Computer Vision Enabled Smart Tray for Central Venous Catheterization Training

Abstract

A Computer Vision enabled Smart Tray (CVST) was designed for use in medical training for Central Venous Catheterization (CVC). The effects of background color on the ability of the computer vision algorithm to distinguish between tools and the tray was investigated. In addition, the computer vision algorithm was evaluated for accuracy in tool detection. Results indicate that a white monochromatic background is the most useful for segregating background from medical tools, and the algorithm was successfully able to detect 5 different CVC tools both individually and as a group in various arrangements, even when tools overlapped or touched. When the system was in error, it was nearly always due to one tool which has a color similar to that of the background. The CVST shows promise as a CVC training tool and demonstrates that computer vision can be used to accurately detect medical tools.

Shifting Perspectives: A proposed framework for analyzing head-mounted eye-tracking data with dynamic areas of interest and dynamic scenes

“…For this application, two separate computer vision models were used. The first computer vision model was previously developed for tracking tools during the use of a medical simulator to give live feedback during training (Brown & Wu, 2022). This model was expanded to also include the computer used in the trainer pictured in Figure 2 .…”