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Image Guided Automation of Endovascular Robotic Surgery

[+] Author Affiliations
Aditya Reddy Ashammagari, Ravikiran Chollangi, Adnan Siddiqui, Kenneth Snyder

University at Buffalo, Buffalo, NY

Naveen Kumar Sankaran, Pramod Chembrammel, Thenkurussi Kesavadas

University of Illinois at Urbana-Champaign, Urbana, IL

Paper No. IMECE2016-65922, pp. V014T07A017; 6 pages
doi:10.1115/IMECE2016-65922
From:
  • ASME 2016 International Mechanical Engineering Congress and Exposition
  • Volume 14: Emerging Technologies; Materials: Genetics to Structures; Safety Engineering and Risk Analysis
  • Phoenix, Arizona, USA, November 11–17, 2016
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5068-8
  • Copyright © 2016 by ASME

abstract

Interventional cardiologists and neurosurgeons are exposed to X-ray radiations while performing surgery. A few tele-robotic systems currently in the market require tedious tele-control using an external input device. In this paper we propose to automate such interventional surgeries using a robotic system using image guided intervention. After image processing of x-ray fluoroscope image and applying new machine learning techniques based on Markov Decision process, our new robotic system is capable of reaching aortic arch, which is the first step in cardiac and neuro-interventional procedures. Further, we explain the algorithm and demonstrate the proposed system implementation on an endovascular simulator.

Copyright © 2016 by ASME
Topics: Robotics , Surgery

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