中心静脉置管训练的计算机视觉智能托盘

Dailen C. Brown, Hang-Ling Wu, Y. Satpathy, Jessica M. Gonzalez-Vargas, Haroula M. Tzamaras, Scarlett R. Miller, J. Moore
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引用次数: 0

摘要

一种计算机视觉智能托盘(CVST)设计用于中心静脉置管(CVC)的医学培训。研究了背景颜色对计算机视觉算法区分工具和托盘能力的影响。此外,还对计算机视觉算法在刀具检测中的精度进行了评价。结果表明,白色单色背景对于从医疗工具中分离背景最有用,并且该算法能够成功地检测到5种不同的CVC工具,无论是单独的还是作为不同排列的一组,即使工具重叠或接触。当系统出错时,几乎总是由于一个工具的颜色与背景相似。CVST显示了作为CVC训练工具的前景,并证明了计算机视觉可以用于准确检测医疗工具。
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Computer Vision Enabled Smart Tray for Central Venous Catheterization Training
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.
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