@inproceedings{b4987c88628647ffaea58020098937c4,
title = "Image-based object state modeling of a transfer task in simulated surgical training",
abstract = "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.",
keywords = "Image understanding, Laparoscopy, Medical simulation, Simulation-based surgical training",
author = "Peng, {Kuo Shiuan} and Minsik Hong and Jerzy Rozenblit",
note = "Funding Information: This work has been supported by the National Science Foundation grant no. 1622589, {"}Computer Guided Laparoscopy Training{"}. Publisher Copyright: {\textcopyright}2017 Society for Modeling & Simulation International (SCS).; 4th Modeling and Simulation in Medicine Symposium, MSM 2017, Part of the 2017 Spring Simulation Multi-Conference, SpringSim 2017 ; Conference date: 23-04-2017 Through 26-04-2017",
year = "2017",
language = "English (US)",
series = "Simulation Series",
publisher = "The Society for Modeling and Simulation International",
number = "6",
pages = "58--69",
editor = "Rozenblit, {Jerzy W.} and Johannes Sametinger",
booktitle = "Simulation Series",
edition = "6",
}