具有目标检测的连续机器人系统用于声带病变诊断的设计

Fan Feng, Zefeng Liu, Yongfeng Cao, Le Xie
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引用次数: 1

摘要

目前,一方面,连续体机器人已广泛应用于机器人辅助微创手术。另一方面,深度学习也广泛应用于医学图像检测和识别。然而,目前还没有机器人系统将这两种技术集成到声带组织病变检测中。因此,本文设计了一种基于螺旋柔性关节的连续诊断声带病变机器人,并推导了主从运动映射方法。此外,我们利用Pytorch框架,利用基于YOLOv5的喉部模型进行了目标检测声带病变的实验。
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Design of A Continuum Robot System with Object Detection for the Diagnosis of Vocal Fold Lesions
Currently, on the one hand, continuum robots have been widely used for robot-assisted minimally invasive surgery. On the other hand, deep learning is also widely used in medical image detection and recognition. However, there is no robotic system that integrates those two technologies for vocal fold tissue lesion detection. Therefore, in this paper, we designed a continuum robot for diagnosing vocal fold lesions based on the helical flexible joint and the master-slave kinematic mapping method is derived. In addition, we conducted experiments on object detection vocal fold lesions using a laryngeal model based on YOLOv5 by using the Pytorch framework.
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