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Merhof, Dorit

Biomedical Engineering / Biomedizinische Technik

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering and the German Society of Biomaterials

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Habibović, Pamela / Haueisen, Jens / Jahnen-Dechent, Wilhelm / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Leonhardt, Steffen / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Boenick, Ulrich / Jaramaz, Branislav / Kraft, Marc / Lenarz, Thomas / Lenthe, Harry / Lo, Benny / Mainardi, Luca / Micera, Silvestro / Penzel, Thomas / Robitzki, Andrea A. / Schaeffter, Tobias / Snedeker, Jess G. / Sörnmo, Leif / Sugano, Nobuhiko / Werner, Jürgen /


IMPACT FACTOR 2018: 1.007
5-year IMPACT FACTOR: 1.390

CiteScore 2018: 1.24

SCImago Journal Rank (SJR) 2018: 0.282
Source Normalized Impact per Paper (SNIP) 2018: 0.831

Online
ISSN
1862-278X
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Volume 61, Issue 5

Issues

Volume 57 (2012)

Video-based detection of device interaction in the operating room

Max Rockstroh
  • Corresponding author
  • Universität Leipzig, Innovation Center Computer Assisted Surgery, Semmelweisstr. 14, D-04103 Leipzig, Germany
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Marco Wittig
  • Universität Leipzig, Innovation Center Computer Assisted Surgery, Semmelweisstr. 14, D-04103 Leipzig, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Stefan Franke
  • Universität Leipzig, Innovation Center Computer Assisted Surgery, Semmelweisstr. 14, D-04103 Leipzig, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jürgen Meixensberger / Thomas Neumuth
  • Universität Leipzig, Innovation Center Computer Assisted Surgery, Semmelweisstr. 14, D-04103 Leipzig, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-12-02 | DOI: https://doi.org/10.1515/bmt-2015-0008

Abstract

The establishment of modern workflow management technologies requires the integration of dated devices. The extraction of the essential device data and usage time spans is a central requirement for an integrated OR environment. Therefore, methods are required that extract such information from the output provided by older generation devices, namely video signals. We developed a four-level approach for video-based device information extraction. Usually, video streams contain all relevant patient data and device usage information. We propose an approach consisting of defining regions of interest, grabbing video signals, analyzing the signals and storing the data in a centralized and structured location. The analysis considers textual information and graphical visualization. A prototype of the analysis approach was implemented and applied to a neurosurgical case. An evaluation study was conducted to measure the performance of the approach on video recordings of real interventions. Three medical devices were considered: intraoperative ultrasound, neuro-navigation and microscope. Overall, recognition rates for device usage higher than 95% were obtained. The approach is not limited to a single surgical discipline and does not require modification of medical devices. Furthermore, the analysis of microscopic video streams expands the detectable aspects of the surgical workflow beyond the recognition of device usage.

Keywords: computer-assisted surgery; intraoperative monitoring; surgery; surgical process model; workflow

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About the article

Corresponding author: Max Rockstroh, Universität Leipzig, Innovation Center Computer Assisted Surgery, Semmelweisstr. 14, D-04103 Leipzig, Germany, E-mail:


Received: 2015-01-16

Accepted: 2015-10-22

Published Online: 2015-12-02

Published in Print: 2016-10-01


Citation Information: Biomedical Engineering / Biomedizinische Technik, Volume 61, Issue 5, Pages 567–576, ISSN (Online) 1862-278X, ISSN (Print) 0013-5585, DOI: https://doi.org/10.1515/bmt-2015-0008.

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