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Smart Tissue Anastomosis Robot (STAR): Accuracy evaluation for supervisory suturing using near-infrared fluorescent markers

机译:智能组织吻合机器人(STAR):使用近红外荧光标记物进行监督缝合的准确性评估

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This paper specifies and evaluates the accuracy of the Smart Tissue Anastomosis Robot (STAR). The STAR is a proof of concept vision-guided robotic system equipped with an actuated laparoscopic suturing tool and a multispectral vision system. The STAR supports image-based suturing commands and is capable of detecting near-infrared fluorescent (NIRF) markers that provide reliable visual segmentation and tracking. The paper reports the best case scenario accuracy specifications of the STAR as derived from its configuration and calibration parameters. We also evaluate experimentally the effects of overlaying NIRF markers on the accuracy of the STAR when these markers are used as the source of image-based commands and we compare these results to the accuracy of the STAR with image-based commands generated from plain color images. Our results demonstrate that the STAR is able to place sutures on a planar phantom with an average accuracy of 0.5 mm with a standard deviation of 0.2 mm and that NIRF markers have no statistically significant adverse effect on the accuracy.
机译:本文指定并评估了智能组织吻合机器人(STAR)的准确性。 STAR是装备有致动腹腔镜缝合工具和多光谱视觉系统的视觉引导机器人系统的证明。 STAR支持基于图像的缝合命令,并且能够检测提供可靠的视觉分割和跟踪的近红外荧光(NIRF)标记。本文报告了从STAR的配置和校准参数得出的最佳情况方案精度指标。当这些标记用作基于图像的命令的来源时,我们还通过实验评估了覆盖NIRF标记对STAR准确性的影响,并将这些结果与STAR的准确性与从纯彩色图像生成的基于图像的命令进行比较。我们的结果表明,STAR能够以0.5 mm的平均精度和0.2 mm的标准偏差将缝合线放置在平面模型上,并且NIRF标记对精度没有统计学上的显着不利影响。

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