Robotic Catheter for Endovascular Surgery Using 3D Magnetic Guidance

  • Amir PournajibEmail author
  • Anup Basu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11010)


Endovascular surgery is an alternative for invasive medical procedures that is becoming widely deployed for many procedures. One of the main challenges of this method is using X-ray before and during the surgery. X-ray side effects are significant for surgeons who are regularly exposed while performing surgeries. Improving the accuracy, efficiency and safety of intra-operative X-rays is very challenging. Furthermore, manual navigation of surgical tools, lack of 3D visualization, and lack of intelligent planning and automatic tracking of the end-effector are critical challenges that have not allowed automatic endovascular surgery to be feasible. In this project, our goal is to develop hardware and software platforms to make a computer assisted robotic surgery system that reduces the need for X-rays during surgery. Also the system can work remotely which means surgeons do not need to be physically next to the patient during an endovascular surgery. The goal is to also overcome the difficulties encountered during manual navigation; and, to improve the speed and experience of performing endovascular surgeries. Experimental results demonstrate the promise and preliminary outcomes of our research.


Endovascular surgery Magnetic sensor Arduino board Catheter 


  1. 1.
    Radaelli, A.G., Peiro, J.: On the segmentation of vascular geometries from medical images. Int. J. Numer. Methods Biomed. Eng. 26(1), 3–34 (2010)CrossRefGoogle Scholar
  2. 2.
    Bekkers, E., Duits, R., Berendschot, T., ter Haar Romeny, B.: A multi-orientation analysis approach to retinal vessel tracking. J. Math. Imaging Vis. 49(3), 583–610 (2014)CrossRefGoogle Scholar
  3. 3.
    Kumar, R.P., Albregtsen, F., Reimers, M., Edwin, B., Langø, T., Elle, O.J.: Three-dimensional blood vessel segmentation and centerline extraction based on two-dimensional cross-section analysis. Ann. Biomed. Eng. 43(5), 1223–1234 (2015)CrossRefGoogle Scholar
  4. 4.
    Mura, M., et al.: A computer-assisted robotic platform for vascular procedures exploiting 3D US-based tracking. Comput. Assist. Surg. 21(1), 63–79 (2016)CrossRefGoogle Scholar
  5. 5.

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Computing ScienceUniversity of AlbertaEdmontonCanada

Personalised recommendations