Safety oriented laparoscopic surgery training system

Andrzej Wytyczak-Partyka, Jan Nikodem, Ryszard Klempous, Jerzy W Rozenblit, Radoslaw Klempous, Imre Rudas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The discussed training system employs several means for encouraging safe behavior during laparoscopic surgery procedures. The elements of no-fly zones, magnetic position sensing and expert systems are tied together to form a complex system that provides guidance and performance assessment. A 3D reconstruction algorithm is used for the purpose of defining no-fly zones and has been tested in a simulator developed for the purpose of this work. An expert system has been built in cooperation with surgeons that, based on simple rules, can assess the risk of the trainee's actions. Despite the shortcomings of the 3D reconstruction process, the training system performed as expected during experiments. Simple exercises like touching points in 3D space were performed and scored appropriately to whether a no-fly zone has been breached or not. Also simple advice could be provided to the trainee in order to help improve the results.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages889-896
Number of pages8
Volume5717 LNCS
DOIs
StatePublished - 2009
Event12th International Conference on Computer Aided Systems Theory, EUROCAST 2009 - Las Palmas de Gran Canaria, Spain
Duration: Feb 15 2009Feb 20 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5717 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Computer Aided Systems Theory, EUROCAST 2009
CountrySpain
CityLas Palmas de Gran Canaria
Period2/15/092/20/09

Fingerprint

Expert systems
Surgery
Safety
3D Reconstruction
Expert System
Large scale systems
Performance Assessment
Simulators
Reconstruction Algorithm
Exercise
Guidance
Complex Systems
Simulator
Sensing
Experiments
Experiment
Training

Keywords

  • Expert system
  • Fuzzy logic
  • Image processing
  • Laparoscopic surgery
  • Training

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Wytyczak-Partyka, A., Nikodem, J., Klempous, R., Rozenblit, J. W., Klempous, R., & Rudas, I. (2009). Safety oriented laparoscopic surgery training system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5717 LNCS, pp. 889-896). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5717 LNCS). https://doi.org/10.1007/978-3-642-04772-5_114

Safety oriented laparoscopic surgery training system. / Wytyczak-Partyka, Andrzej; Nikodem, Jan; Klempous, Ryszard; Rozenblit, Jerzy W; Klempous, Radoslaw; Rudas, Imre.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5717 LNCS 2009. p. 889-896 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5717 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wytyczak-Partyka, A, Nikodem, J, Klempous, R, Rozenblit, JW, Klempous, R & Rudas, I 2009, Safety oriented laparoscopic surgery training system. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5717 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5717 LNCS, pp. 889-896, 12th International Conference on Computer Aided Systems Theory, EUROCAST 2009, Las Palmas de Gran Canaria, Spain, 2/15/09. https://doi.org/10.1007/978-3-642-04772-5_114
Wytyczak-Partyka A, Nikodem J, Klempous R, Rozenblit JW, Klempous R, Rudas I. Safety oriented laparoscopic surgery training system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5717 LNCS. 2009. p. 889-896. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-04772-5_114
Wytyczak-Partyka, Andrzej ; Nikodem, Jan ; Klempous, Ryszard ; Rozenblit, Jerzy W ; Klempous, Radoslaw ; Rudas, Imre. / Safety oriented laparoscopic surgery training system. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5717 LNCS 2009. pp. 889-896 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{05e616074df94aa9a4b76f5ecdf18d85,
title = "Safety oriented laparoscopic surgery training system",
abstract = "The discussed training system employs several means for encouraging safe behavior during laparoscopic surgery procedures. The elements of no-fly zones, magnetic position sensing and expert systems are tied together to form a complex system that provides guidance and performance assessment. A 3D reconstruction algorithm is used for the purpose of defining no-fly zones and has been tested in a simulator developed for the purpose of this work. An expert system has been built in cooperation with surgeons that, based on simple rules, can assess the risk of the trainee's actions. Despite the shortcomings of the 3D reconstruction process, the training system performed as expected during experiments. Simple exercises like touching points in 3D space were performed and scored appropriately to whether a no-fly zone has been breached or not. Also simple advice could be provided to the trainee in order to help improve the results.",
keywords = "Expert system, Fuzzy logic, Image processing, Laparoscopic surgery, Training",
author = "Andrzej Wytyczak-Partyka and Jan Nikodem and Ryszard Klempous and Rozenblit, {Jerzy W} and Radoslaw Klempous and Imre Rudas",
year = "2009",
doi = "10.1007/978-3-642-04772-5_114",
language = "English (US)",
isbn = "3642047718",
volume = "5717 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "889--896",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Safety oriented laparoscopic surgery training system

AU - Wytyczak-Partyka, Andrzej

AU - Nikodem, Jan

AU - Klempous, Ryszard

AU - Rozenblit, Jerzy W

AU - Klempous, Radoslaw

AU - Rudas, Imre

PY - 2009

Y1 - 2009

N2 - The discussed training system employs several means for encouraging safe behavior during laparoscopic surgery procedures. The elements of no-fly zones, magnetic position sensing and expert systems are tied together to form a complex system that provides guidance and performance assessment. A 3D reconstruction algorithm is used for the purpose of defining no-fly zones and has been tested in a simulator developed for the purpose of this work. An expert system has been built in cooperation with surgeons that, based on simple rules, can assess the risk of the trainee's actions. Despite the shortcomings of the 3D reconstruction process, the training system performed as expected during experiments. Simple exercises like touching points in 3D space were performed and scored appropriately to whether a no-fly zone has been breached or not. Also simple advice could be provided to the trainee in order to help improve the results.

AB - The discussed training system employs several means for encouraging safe behavior during laparoscopic surgery procedures. The elements of no-fly zones, magnetic position sensing and expert systems are tied together to form a complex system that provides guidance and performance assessment. A 3D reconstruction algorithm is used for the purpose of defining no-fly zones and has been tested in a simulator developed for the purpose of this work. An expert system has been built in cooperation with surgeons that, based on simple rules, can assess the risk of the trainee's actions. Despite the shortcomings of the 3D reconstruction process, the training system performed as expected during experiments. Simple exercises like touching points in 3D space were performed and scored appropriately to whether a no-fly zone has been breached or not. Also simple advice could be provided to the trainee in order to help improve the results.

KW - Expert system

KW - Fuzzy logic

KW - Image processing

KW - Laparoscopic surgery

KW - Training

UR - http://www.scopus.com/inward/record.url?scp=78651255871&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78651255871&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-04772-5_114

DO - 10.1007/978-3-642-04772-5_114

M3 - Conference contribution

AN - SCOPUS:78651255871

SN - 3642047718

SN - 9783642047718

VL - 5717 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 889

EP - 896

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -