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NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics

PURPOSE: NiftySim, an open-source finite element toolkit, has been designed to allow incorporation of high-performance soft tissue simulation capabilities into biomedical applications. The toolkit provides the option of execution on fast graphics processing unit (GPU) hardware, numerous constitutive...

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Autores principales: Johnsen, Stian F., Taylor, Zeike A., Clarkson, Matthew J., Hipwell, John, Modat, Marc, Eiben, Bjoern, Han, Lianghao, Hu, Yipeng, Mertzanidou, Thomy, Hawkes, David J., Ourselin, Sebastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4488488/
https://www.ncbi.nlm.nih.gov/pubmed/25241111
http://dx.doi.org/10.1007/s11548-014-1118-5
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author Johnsen, Stian F.
Taylor, Zeike A.
Clarkson, Matthew J.
Hipwell, John
Modat, Marc
Eiben, Bjoern
Han, Lianghao
Hu, Yipeng
Mertzanidou, Thomy
Hawkes, David J.
Ourselin, Sebastien
author_facet Johnsen, Stian F.
Taylor, Zeike A.
Clarkson, Matthew J.
Hipwell, John
Modat, Marc
Eiben, Bjoern
Han, Lianghao
Hu, Yipeng
Mertzanidou, Thomy
Hawkes, David J.
Ourselin, Sebastien
author_sort Johnsen, Stian F.
collection PubMed
description PURPOSE: NiftySim, an open-source finite element toolkit, has been designed to allow incorporation of high-performance soft tissue simulation capabilities into biomedical applications. The toolkit provides the option of execution on fast graphics processing unit (GPU) hardware, numerous constitutive models and solid-element options, membrane and shell elements, and contact modelling facilities, in a simple to use library. METHODS: The toolkit is founded on the total Lagrangian explicit dynamics (TLEDs) algorithm, which has been shown to be efficient and accurate for simulation of soft tissues. The base code is written in C[Formula: see text] , and GPU execution is achieved using the nVidia CUDA framework. In most cases, interaction with the underlying solvers can be achieved through a single Simulator class, which may be embedded directly in third-party applications such as, surgical guidance systems. Advanced capabilities such as contact modelling and nonlinear constitutive models are also provided, as are more experimental technologies like reduced order modelling. A consistent description of the underlying solution algorithm, its implementation with a focus on GPU execution, and examples of the toolkit’s usage in biomedical applications are provided. RESULTS: Efficient mapping of the TLED algorithm to parallel hardware results in very high computational performance, far exceeding that available in commercial packages. CONCLUSION: The NiftySim toolkit provides high-performance soft tissue simulation capabilities using GPU technology for biomechanical simulation research applications in medical image computing, surgical simulation, and surgical guidance applications.
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spelling pubmed-44884882015-07-07 NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics Johnsen, Stian F. Taylor, Zeike A. Clarkson, Matthew J. Hipwell, John Modat, Marc Eiben, Bjoern Han, Lianghao Hu, Yipeng Mertzanidou, Thomy Hawkes, David J. Ourselin, Sebastien Int J Comput Assist Radiol Surg Original Article PURPOSE: NiftySim, an open-source finite element toolkit, has been designed to allow incorporation of high-performance soft tissue simulation capabilities into biomedical applications. The toolkit provides the option of execution on fast graphics processing unit (GPU) hardware, numerous constitutive models and solid-element options, membrane and shell elements, and contact modelling facilities, in a simple to use library. METHODS: The toolkit is founded on the total Lagrangian explicit dynamics (TLEDs) algorithm, which has been shown to be efficient and accurate for simulation of soft tissues. The base code is written in C[Formula: see text] , and GPU execution is achieved using the nVidia CUDA framework. In most cases, interaction with the underlying solvers can be achieved through a single Simulator class, which may be embedded directly in third-party applications such as, surgical guidance systems. Advanced capabilities such as contact modelling and nonlinear constitutive models are also provided, as are more experimental technologies like reduced order modelling. A consistent description of the underlying solution algorithm, its implementation with a focus on GPU execution, and examples of the toolkit’s usage in biomedical applications are provided. RESULTS: Efficient mapping of the TLED algorithm to parallel hardware results in very high computational performance, far exceeding that available in commercial packages. CONCLUSION: The NiftySim toolkit provides high-performance soft tissue simulation capabilities using GPU technology for biomechanical simulation research applications in medical image computing, surgical simulation, and surgical guidance applications. Springer Berlin Heidelberg 2014-09-21 2015 /pmc/articles/PMC4488488/ /pubmed/25241111 http://dx.doi.org/10.1007/s11548-014-1118-5 Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Original Article
Johnsen, Stian F.
Taylor, Zeike A.
Clarkson, Matthew J.
Hipwell, John
Modat, Marc
Eiben, Bjoern
Han, Lianghao
Hu, Yipeng
Mertzanidou, Thomy
Hawkes, David J.
Ourselin, Sebastien
NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics
title NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics
title_full NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics
title_fullStr NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics
title_full_unstemmed NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics
title_short NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics
title_sort niftysim: a gpu-based nonlinear finite element package for simulation of soft tissue biomechanics
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4488488/
https://www.ncbi.nlm.nih.gov/pubmed/25241111
http://dx.doi.org/10.1007/s11548-014-1118-5
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