实现自主机器人胃镜检查,采用全新的干预关键点和多检测系统
Yuying Liu1, Guang Feng1, Qi He1
1Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, China.
Computer methods and programs in biomedicine
|August 19, 2025
概括
这项研究引入了用于自主机器人胃镜的AI框架,改进了多体检测和导航. 该系统显示高精度,提高了胃疾病的诊断能力.
科学领域:
- 医疗机器人 医疗机器人
- 人工智能的人工智能
- 胃肠病学 胃肠病学
背景情况:
- 胃癌面临着重大的全球健康挑战.
- 传统的胃镜术严重依赖内镜师的专业知识,限制了准确性和稳定性.
- 机器人胃镜为改善上部胃肠道疾病查提供了一个有希望的解决方案.
研究的目的:
- 开发一个人工智能驱动的框架,用于自主机器人胃镜.
- 增强自主导航和胃镜诊断能力.
- 提高胃病识别的准确性和一致性.
主要方法:
- 提出了一个深度学习框架,集成关键点和聚检测 (KP-YOLO).
- 开发并使用了两个注释数据集:真实胃镜图像 (3,454) 和UGI幻影图像 (2,144).
- 在UGI幻影机上使用机器人手臂,运动控制和奥林巴斯内镜系统验证了系统.
主要成果:
- 检测模型实现了干预关键点的高精度 (P) 和平均平均精度 (mAP) (P=0.987,mAP=0.985).
- 多胞胎检测性能也非常出色 (P=0.994,mAP=0.964).
- 实验验证证了该系统在高保真UGI幻影机上的有效性.
结论:
- 由人工智能引导的机器人胃镜成功展示了自主干预导航和智能聚检测.
- 这种AI框架显著提高了机器人胃镜的自主性和智能性.
- 这些发现支持智能机器人胃镜未来临床应用的潜力.
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