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以点云为指导的超声波机器人扫描为脏的路径规划,基于解剖学定位
Chunyi Wu1, Hu Lan1, Jijie Ma1
1College of Engineering, Zhejiang Normal University, Jinhua, 321000, China.
Computers in biology and medicine
|April 22, 2025
概括
这项研究介绍了一种自动路径规划算法,用于执行脏超声波的超声波机器人. 该方法使用解剖学地标和3D点云数据进行精确的脏成像,成功率为93.33%.
科学领域:
- 医疗机器人 医疗机器人
- 医疗成像医学成像
- 计算机视觉 计算机视觉
背景情况:
- 脏超声波路径规划对超声波机器人提出了挑战.
- 目前的方法可能缺乏精度和自动化,特别是在不同患者姿势的情况下.
研究的目的:
- 开发和验证超声波机器人引导脏超声波专用路径规划算法.
- 通过使用解剖定位和点云技术,提高脏成像的自动化和准确性.
主要方法:
- 使用深度摄像头进行3D点云数据采集和预处理.
- 综合的解剖学地标识别 (脊柱线,腰部,腰部与脊柱角) 用于模型定向和轨迹规划.
- 通过模拟和对人类受试者的自动扫描验证了算法.
主要成果:
- 该算法成功地为各种人类模型和姿势计划了扫描路径.
- 超声波机器人在从志愿者那里获得脏图像的成功率达到了93.33%.
- 平均扫描时间减少到4.28秒.
结论:
- 拟议的方法通过结合解剖特征,有效地规划脏超声波扫描路径.
- 点云技术可以实现低成本的自动扫描,减少对外部标记物的依赖.
- 算法地址带来了变化挑战,为自主超声波机器人操作铺平了道路.
相关概念视频
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