A deep learning framework for real-time 3D model registration in robot-assisted laparoscopic surgery.

Journal: The international journal of medical robotics + computer assisted surgery : MRCAS
Published Date: Mar 13, 2022

Abstract

INTRODUCTION: The current study presents a deep learning framework to determine, in real-time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real counterpart. The resulting augmented video flow is streamed back to the surgeon as a support during laparoscopic robot-assisted procedures.

Authors

  • Erica Padovan
    Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy.
  • Giorgia Marullo
    Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy.
  • Leonardo Tanzi
    DIGEP, Polytechnic University of Turin, Torino, Italy.
  • Pietro Piazzolla
    Department of Management and Production Engineer, Politechnic University of Turin, Turin, Italy.
  • Sandro Moos
    Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy.
  • Francesco Porpiglia
    Division of Urology, Department of Oncology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, Turin, Italy.
  • Enrico Vezzetti
    Department of Management and Production Engineer, Politechnic University of Turin, Turin, Italy.

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