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Robust Laparoscopic Instruments Tracking Using Colored Strips

  • Virginia MamoneEmail author
  • Rosanna Maria Viglialoro
  • Fabrizio Cutolo
  • Filippo Cavallo
  • Simone Guadagni
  • Vincenzo Ferrari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10325)

Abstract

To assist surgeons in the acquisition of the required skills for the proper execution of the laparoscopic procedure, surgical simulators are used. During training with simulators it is useful to provide a surgical performance quantitative evaluation. Recent research works showed that such evaluation can be obtained by tracking the laparoscopic instruments, using only the images provided by the laparoscope and without hindering the surgical scene. In this work the state of the art method is improved so that a robust tracking can run even with the noisy background provided by realistic simulators. The method was validated by comparison with the tracking of a “chess-board” pattern and following tests were performed to check the robustness of the developed algorithm. Despite the noisy environment, the implemented method was found to be able to track the tip of the surgical instrument with a good accuracy compared to the other studies in the literature.

Keywords

Optical tracking Single camera Laparoscopic training Surgical simulation Surgical performance evaluation 

Notes

Acknowledgement

This research work was supported by VALVETECH project, FAS fund – Tuscany Region (Realization of a newly developed polymeric aortic valve, implantable through robotic platform with minimally invasive surgical techniques) and SThARS project, grant “Ricerca finalizzata e Giovani ricercatori 2011–2012” Young Researchers - Italian Ministry of Health (Surgical Training in identification and isolation of deformable tubular structures with hybrid Augmented Reality Simulation).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Virginia Mamone
    • 1
    Email author
  • Rosanna Maria Viglialoro
    • 1
    • 2
  • Fabrizio Cutolo
    • 1
  • Filippo Cavallo
    • 3
  • Simone Guadagni
    • 4
  • Vincenzo Ferrari
    • 1
    • 5
  1. 1.EndoCAS, Department of Translational Research and of New Surgical and Medical TechnologiesUniversity of PisaPisaItaly
  2. 2.Vascular Surgery UnitCisanello University Hospital AOUPPisaItaly
  3. 3.Sant’Anna School of Advanced StudiesPisaItaly
  4. 4.General Surgery Unit, Department of Oncology Transplantation and New TechnologiesUniversity of PisaPisaItaly
  5. 5.Department of Information EngineeringUniversity of PisaPisaItaly

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