Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions.

Journal: International journal of computer assisted radiology and surgery
Published Date: Oct 8, 2015

Abstract

PURPOSE: Advances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room.

Authors

  • Yohannes Kassahun
    Robotics Innovation Center, German Research Center for Artificial Intelligence, Robert-Hooke-Str. 1, 28359, Bremen, Germany. yohannes.kassahun@dfki.de.
  • Bingbin Yu
    Faculty 3 - Mathematics and Computer Science, University of Bremen, Robert-Hooke-Str. 1, 28359, Bremen, Germany.
  • Abraham Temesgen Tibebu
    Faculty 3 - Mathematics and Computer Science, University of Bremen, Robert-Hooke-Str. 1, 28359, Bremen, Germany.
  • Danail Stoyanov
    University College London, London, UK.
  • Stamatia Giannarou
    Hamlyn Centre of Robotic Surgery, Department of Surgery and Cancer Imperial College London London UK.
  • Jan Hendrik Metzen
    Faculty 3 - Mathematics and Computer Science, University of Bremen, Robert-Hooke-Str. 1, 28359, Bremen, Germany.
  • Emmanuel Vander Poorten
    Department of Mechanical Engineering, University of Leuven, Celestijnenlaan 300B, 3001, Heverlee, Belgium.

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