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A Framework for Automating Interventional Surgeries (Catheter detection and Automation of a crucial step in Percutaneous Coronary Interventional surgery - PCI).

机译:介入手术自动化框架(经皮冠状动脉介入手术关键步骤的导管检测和自动化-PCI)。

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摘要

Interventional Cardiologists and Neuro-surgeons are facing a grave danger daily by being exposed to X-ray radiations while performing surgery. A few robotic systems exist in the market to aid them. This work is a first step for automating such interventional surgeries using robotic systems capable of navigating standard surgical guide wires and catheters. Reaching the Bovine Aortic Arch is the first step after selection of the required guide wire and catheter for most of the interventional procedures. In this paper guide lines are developed for the robotic system to perform the procedure of advancing a guide catheter into the aortic arch, following an optimal path automatically, using image based catheter (Simmons 22 catheter) detection in X-ray images taken from a surgery trainer (VIST simulator -- Mentice AB). The X-ray imagery is captured by a camera and the images obtained are pre-processed and the guidewire/catheter is recognized using a level by level thresholding technique. This data is fed to a Kalman filter to enhance the recognition rate. This work also shows that the surgical tasks can be learned and automated such that the use of radioactive dye inside the patient body can be reduced. Thus reducing the radiation dangers to the patient.
机译:介入心脏病专家和神经外科医生每天都在进行手术时暴露于X射线辐射下面临严重的危险。市场上有一些机器人系统可以帮助他们。这项工作是使用能够导航标准手术导丝和导管的机器人系统使此类介入手术自动化的第一步。在大多数介入手术中,选择所需的导丝和导管后,第一步就是要到达牛主动脉弓。在本文中,为机器人系统开发了一些指导线,以执行引导导管进入自动主动脉弓的过程,并根据最佳路径自动进行操作,并使用基于图像的导管(Simmons 22导管)对从手术中获取的X射线图像进行检测培训师(VIST模拟器-Mentice AB)。 X射线图像由照相机捕获,并对获得的图像进行预处理,并使用逐级阈值化技术识别导丝/导管。该数据被馈送到卡尔曼滤波器以提高识别率。这项工作还表明,可以学习和自动化外科手术任务,从而可以减少患者体内放射性染料的使用。因此减少了对患者的辐射危险。

著录项

  • 作者

    Ashammagari, Aditya Reddy.;

  • 作者单位

    State University of New York at Buffalo.;

  • 授予单位 State University of New York at Buffalo.;
  • 学科 Engineering Mechanical.;Computer Science.;Artificial Intelligence.
  • 学位 M.S.
  • 年度 2013
  • 页码 84 p.
  • 总页数 84
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:41:38

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