使用基于图像的血流检测的自主机器人抽吸以清除手术区域用于止血
Autonomous Robotic Suction to Clear the Surgical Field for Hemostasis using Image-based Blood Flow Detection
摘要：
自主机器人手术在过去十年中取得了重大进展，其目的是减少外科医生的疲劳，提高手术的一致性，也许有一天会接管手术本身。然而，自动化尚未应用于控制组织和血管出血的关键外科任务-即止血。止血的任务涵盖一系列出血源和一系列血液速度、轨迹和体积。在极端情况下，不受控制的血管会使手术区域充满流动的血液。在这项工作中，我们提出了第一个自动化的止血解决方案，通过开发一种新的概率血流检测算法和轨迹生成技术，引导自主吸引工具汇集血液。在模拟场景和涉及甲状腺切除术期间发生出血的真实创伤场景中测试血流检测算法。完整的解决方案在物理实验室环境中使用达芬奇研究套件（dVRK）和模拟手术腔进行测试，以供血液流过。结果表明，我们的自动化解决方案具有准确的检测，快速的反应时间，并有效地去除流动的血液。因此，所提出的方法是清理手术区域的有力工具，外科医生或未来的机器人自动化开发可以遵循这些工具来闭合血管破裂。
英文摘要：
Autonomous robotic surgery has seen significant progression over the last decade with the aims of reducing surgeon fatigue, improving procedural consistency, and perhaps one day take over surgery itself. However, automation has not been applied to the critical surgical task of controlling tissue and blood vessel bleeding--known as hemostasis. The task of hemostasis covers a spectrum of bleeding sources and a range of blood velocity, trajectory, and volume. In an extreme case, an un-controlled blood vessel fills the surgical field with flowing blood. In this work, we present the first, automated solution for hemostasis through development of a novel probabilistic blood flow detection algorithm and a trajectory generation technique that guides autonomous suction tools towards pooling blood. The blood flow detection algorithm is tested in both simulated scenes and in a real-life trauma scenario involving a hemorrhage that occurred during thyroidectomy. The complete solution is tested in a physical lab setting with the da Vinci Research Kit (dVRK) and a simulated surgical cavity for blood to flow through. The results show that our automated solution has accurate detection, a fast reaction time, and effective removal of the flowing blood. Therefore, the proposed methods are powerful tools to clearing the surgical field which can be followed by either a surgeon or future robotic automation developments to close the vessel rupture.
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