Image-based object state modeling of a transfer task in simulated surgical training

Kuo Shiuan Peng, Minsik Hong, Jerzy W Rozenblit

Research output: Contribution to journalArticle


This paper proposes a real-time, image-based training scenario comprehension method. This method aims to support the visual and haptic guidance system for laparoscopic surgery skill training. The target task of the proposed approach is a simulation model of a peg transfer task, which is one of the hands-on exam topics in the Fundamentals of Laparoscopic Surgery certification. In this paper, a simulation process of an image-based object state modeling method is proposed. It generates a system object state of the transfer task to support the guidance system. A rule-based, intelligent system is used to discern the object state without the aid of any object template or model. This is the novelty of the proposed method.

Original languageEnglish (US)
Pages (from-to)58-69
Number of pages12
JournalSimulation Series
Issue number6
StatePublished - 2017


  • Image understanding
  • Laparoscopy
  • Medical simulation
  • Simulation-based surgical training

ASJC Scopus subject areas

  • Computer Networks and Communications

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