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肋骨区域检测用于扫描路径规划,用于全自动化机器人腹部超声波
Koudai Okuzaki1,2, Norihiro Koizumi2, Kiyoshi Yoshinaka1
1Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan.
International journal of computer assisted radiology and surgery
|October 3, 2023
概括
这项研究开发了一种新的方法,使用深度差异成像和呼吸变异来准确地估计自动化机器人超声波 (US) 系统的肋骨区域,改善胆道扫描路径规划.
科学领域:
- 医疗机器人 医疗机器人
- 医疗成像医学成像
- 超声波技术 超声波技术 超声波技术
背景情况:
- 自动超声波机器人需要精确的扫描路径规划.
- 识别下腰带边界标志对于胆管US扫描至关重要,但由于不可见性,通常具有挑战性.
- 准确的肋骨区域估计对于强大的机器人美国导航至关重要.
研究的目的:
- 开发一种非侵入性方法来估计肋骨区域,用于自动化机器人超声波扫描路径规划.
- 为了能够准确地识别肋下边界,以改善胆道成像.
- 推进美国全自动化机器人系统的能力.
主要方法:
- 提出了一种利用RGB-D图像和呼吸变化的新方法.
- 通过比较不同呼吸阶段的图像来生成深度差异成像,以突出显示肋骨区域.
- YOLOv5物体检测模型被训练在深度差图像上,以确定肋下边界.
主要成果:
- 拟议的方法在健康受试者中实现了0.951的高交叉与结合 (IoU) 和0.77的平均信心.
- 预测和地面真相位置之间的平均3D空间误差为16.5毫米.
- 使用深度差成像的肋骨检测显著优于仅依赖RGB图像的方法.
结论:
- 深度差成像技术准确地估计了肋骨区域的非侵入性,没有医生的干预.
- 这种方法增强了机器人超声波的扫描路径规划,特别是胆道成像.
- 这些发现有助于开发更有能力和自动化的美国机器人系统.
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