Article

Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions

Authors:

Peter A. N. Bosman,

Tanja AlderliestenAuthors Info & Claims

GECCO '05: Proceedings of the 7th annual workshop on Genetic and evolutionary computation

Pages 125 - 132

https://doi.org/10.1145/1102256.1102286

Published: 25 June 2005 Publication History

Abstract

To obtain the expertise to correctly perform minimally-invasive vascular interventions thorough training is required. Training using simulation systems are increasingly becoming an accepted methodology. Recently, a minimally--invasive vascular intervention simulation (MIVIS) system has been developed. At the heart of this system lies an optimization problem to be solved repeatedly. In this paper, we investigate the advantages and disadvantages of using an evolutionary algorithm (EA) to solve the optimization problem instead of a problem--specific first--order analytical approximation algorithm. The results show that the use of the EA as optimization algorithm is favorable. A substantial reduction in time can be obtained while the RMS error associated with the simulation result differs only slightly.

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Cited By

Baier-Saip JBaier POliveira JBaier H(2018)Higher-Order Approximation to the Guidewire Model Used in Simulators of Cardiac Catheterization and Multiple Segment RelaxationsPresence: Teleoperators and Virtual Environments10.1162/pres_a_0033427:4(333-360)Online publication date: 1-Nov-2018
https://doi.org/10.1162/pres_a_00334
Gray CAl-Maliki SVidal F(2018)Data exploration in evolutionary reconstruction of PET imagesGenetic Programming and Evolvable Machines10.1007/s10710-018-9330-719:3(391-419)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s10710-018-9330-7
Ouaddah ABoughaci D(2014)A New Method to Improve Quality of Reconstructed Images in TomographyComputational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications10.1007/978-3-319-09994-1_26(267-272)Online publication date: 2014
https://doi.org/10.1007/978-3-319-09994-1_26
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Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions

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cover image ACM Conferences

GECCO '05: Proceedings of the 7th annual workshop on Genetic and evolutionary computation

June 2005

431 pages

ISBN:9781450378000

DOI:10.1145/1102256

Conference Chair:
Franz Rothlauf
University of Mannheim, Germany

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

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Published: 25 June 2005

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GECCO05: Genetic and Evolutionary Computation Conference

June 25 - 26, 2005

D.C., Washington

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Baier-Saip JBaier POliveira JBaier H(2018)Higher-Order Approximation to the Guidewire Model Used in Simulators of Cardiac Catheterization and Multiple Segment RelaxationsPresence: Teleoperators and Virtual Environments10.1162/pres_a_0033427:4(333-360)Online publication date: 1-Nov-2018
https://doi.org/10.1162/pres_a_00334
Gray CAl-Maliki SVidal F(2018)Data exploration in evolutionary reconstruction of PET imagesGenetic Programming and Evolvable Machines10.1007/s10710-018-9330-719:3(391-419)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s10710-018-9330-7
Ouaddah ABoughaci D(2014)A New Method to Improve Quality of Reconstructed Images in TomographyComputational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications10.1007/978-3-319-09994-1_26(267-272)Online publication date: 2014
https://doi.org/10.1007/978-3-319-09994-1_26
Ouaddah ABoughaci D(2014)Local Search Method for Image Reconstruction with Same Concentration in TomographyAdvances in Signal Processing and Intelligent Recognition Systems10.1007/978-3-319-04960-1_30(335-346)Online publication date: 2014
https://doi.org/10.1007/978-3-319-04960-1_30
Ji CHou ZXie X(2011)Guidewire navigation and delivery system for robot-assisted cardiology interventionsIEEE 10th International Conference on Cognitive Informatics and Cognitive Computing (ICCI-CC'11)10.1109/COGINF.2011.6016161(330-335)Online publication date: Aug-2011
https://doi.org/10.1109/COGINF.2011.6016161
Vidal FLazaro-Ponthus DLegoupil SLouchet JLutton ÉRocchisani J(2010)Artificial Evolution for 3D PET ReconstructionArtifical Evolution10.1007/978-3-642-14156-0_4(37-48)Online publication date: 2010
https://doi.org/10.1007/978-3-642-14156-0_4
Vidal FLouchet JRocchisani JLutton É(2010)New genetic operators in the fly algorithmProceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I10.1007/978-3-642-12239-2_30(292-301)Online publication date: 7-Apr-2010
https://dl.acm.org/doi/10.1007/978-3-642-12239-2_30
Spillmann JHarders M(2010)Inextensible elastic rods with torsional friction based on Lagrange multipliersComputer Animation and Virtual Worlds10.1002/cav.36221:6(561-572)Online publication date: 1-Nov-2010
https://dl.acm.org/doi/10.1002/cav.362
Vidal FLazaro-Ponthus DLegoupil SLouchet JLutton ÉRocchisani J(2009)Artificial evolution for 3D PET reconstructionProceedings of the 9th international conference on Artificial evolution10.5555/1883723.1883730(37-48)Online publication date: 26-Oct-2009
https://dl.acm.org/doi/10.5555/1883723.1883730
Vidal FLouchet JRocchisani JLutton E(2009)PET reconstruction using a cooperative coevolution strategy in LOR space2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC)10.1109/NSSMIC.2009.5401758(3363-3366)Online publication date: Oct-2009
https://doi.org/10.1109/NSSMIC.2009.5401758
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