An electromechanical based deformable model for soft tissue simulation.
Identifieur interne : 001210 ( PubMed/Corpus ); précédent : 001209; suivant : 001211An electromechanical based deformable model for soft tissue simulation.
Auteurs : Yongmin Zhong ; Bijan Shirinzadeh ; Julian Smith ; Chengfan GuSource :
- Artificial intelligence in medicine [ 1873-2860 ] ; 2009.
English descriptors
- KwdEn :
- MESH :
Abstract
Soft tissue deformation is of great importance to surgery simulation. Although a significant amount of research efforts have been dedicated to simulating the behaviours of soft tissues, modelling of soft tissue deformation is still a challenging problem. This paper presents a new deformable model for simulation of soft tissue deformation from the electromechanical viewpoint of soft tissues.
DOI: 10.1016/j.artmed.2009.08.003
PubMed: 19819116
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pubmed:19819116Le document en format XML
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<author><name sortKey="Zhong, Yongmin" sort="Zhong, Yongmin" uniqKey="Zhong Y" first="Yongmin" last="Zhong">Yongmin Zhong</name>
<affiliation><nlm:affiliation>Department of Mechanical Engineering, Curtin University of Technology, GPO Box U1987, Perth, WA 6845, Australia. Y.Zhong@curtin.edu.au</nlm:affiliation>
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<author><name sortKey="Shirinzadeh, Bijan" sort="Shirinzadeh, Bijan" uniqKey="Shirinzadeh B" first="Bijan" last="Shirinzadeh">Bijan Shirinzadeh</name>
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<author><name sortKey="Smith, Julian" sort="Smith, Julian" uniqKey="Smith J" first="Julian" last="Smith">Julian Smith</name>
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<author><name sortKey="Gu, Chengfan" sort="Gu, Chengfan" uniqKey="Gu C" first="Chengfan" last="Gu">Chengfan Gu</name>
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<author><name sortKey="Zhong, Yongmin" sort="Zhong, Yongmin" uniqKey="Zhong Y" first="Yongmin" last="Zhong">Yongmin Zhong</name>
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<author><name sortKey="Shirinzadeh, Bijan" sort="Shirinzadeh, Bijan" uniqKey="Shirinzadeh B" first="Bijan" last="Shirinzadeh">Bijan Shirinzadeh</name>
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<author><name sortKey="Smith, Julian" sort="Smith, Julian" uniqKey="Smith J" first="Julian" last="Smith">Julian Smith</name>
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<author><name sortKey="Gu, Chengfan" sort="Gu, Chengfan" uniqKey="Gu C" first="Chengfan" last="Gu">Chengfan Gu</name>
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<series><title level="j">Artificial intelligence in medicine</title>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Artificial Intelligence</term>
<term>Biomechanical Phenomena</term>
<term>Computer Graphics</term>
<term>Computer Simulation</term>
<term>Connective Tissue (anatomy & histology)</term>
<term>Elasticity</term>
<term>Feedback</term>
<term>Humans</term>
<term>Imaging, Three-Dimensional</term>
<term>Models, Biological</term>
<term>Pliability</term>
<term>Stress, Mechanical</term>
<term>Surgical Procedures, Operative</term>
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<keywords scheme="MESH" qualifier="anatomy & histology" xml:lang="en"><term>Connective Tissue</term>
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<front><div type="abstract" xml:lang="en">Soft tissue deformation is of great importance to surgery simulation. Although a significant amount of research efforts have been dedicated to simulating the behaviours of soft tissues, modelling of soft tissue deformation is still a challenging problem. This paper presents a new deformable model for simulation of soft tissue deformation from the electromechanical viewpoint of soft tissues.</div>
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<DateCompleted><Year>2010</Year>
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<Title>Artificial intelligence in medicine</Title>
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<ArticleTitle>An electromechanical based deformable model for soft tissue simulation.</ArticleTitle>
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<Abstract><AbstractText Label="OBJECTIVE" NlmCategory="OBJECTIVE">Soft tissue deformation is of great importance to surgery simulation. Although a significant amount of research efforts have been dedicated to simulating the behaviours of soft tissues, modelling of soft tissue deformation is still a challenging problem. This paper presents a new deformable model for simulation of soft tissue deformation from the electromechanical viewpoint of soft tissues.</AbstractText>
<AbstractText Label="METHODS AND MATERIAL" NlmCategory="METHODS">Soft tissue deformation is formulated as a reaction-diffusion process coupled with a mechanical load. The mechanical load applied to a soft tissue to cause a deformation is incorporated into the reaction-diffusion system, and consequently distributed among mass points of the soft tissue. Reaction-diffusion of mechanical load and non-rigid mechanics of motion are combined to govern the simulation dynamics of soft tissue deformation.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">An improved reaction-diffusion model is developed to describe the distribution of the mechanical load in soft tissues. A three-layer artificial cellular neural network is constructed to solve the reaction-diffusion model for real-time simulation of soft tissue deformation. A gradient based method is established to derive internal forces from the distribution of the mechanical load. Integration with a haptic device has also been achieved to simulate soft tissue deformation with haptic feedback.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">The proposed methodology does not only predict the typical behaviours of living tissues, but it also accepts both local and large-range deformations. It also accommodates isotropic, anisotropic and inhomogeneous deformations by simple modification of diffusion coefficients.</AbstractText>
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<Author ValidYN="Y"><LastName>Gu</LastName>
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