Suite of finite element algorithms for accurate computation of soft tissue deformation for surgical simulation.
Identifieur interne : 001346 ( PubMed/Corpus ); précédent : 001345; suivant : 001347Suite of finite element algorithms for accurate computation of soft tissue deformation for surgical simulation.
Auteurs : Grand Roman Joldes ; Adam Wittek ; Karol MillerSource :
- Medical image analysis [ 1361-8423 ] ; 2009.
English descriptors
- KwdEn :
- Algorithms, Animals, Computer Simulation, Connective Tissue (anatomy & histology), Connective Tissue (physiology), Elastic Modulus (physiology), Finite Element Analysis, Humans, Image Interpretation, Computer-Assisted (methods), Models, Anatomic, Models, Biological, Sensitivity and Specificity, Surgery, Computer-Assisted (methods), Viscosity.
- MESH :
- anatomy & histology : Connective Tissue.
- methods : Image Interpretation, Computer-Assisted, Surgery, Computer-Assisted.
- physiology : Connective Tissue, Elastic Modulus.
- Algorithms, Animals, Computer Simulation, Finite Element Analysis, Humans, Models, Anatomic, Models, Biological, Sensitivity and Specificity, Viscosity.
Abstract
Real time computation of soft tissue deformation is important for the use of augmented reality devices and for providing haptic feedback during operation or surgeon training. This requires algorithms that are fast, accurate and can handle material nonlinearities and large deformations. A set of such algorithms is presented in this paper, starting with the finite element formulation and the integration scheme used and addressing common problems such as hourglass control and locking. The computation examples presented prove that by using these algorithms, real time computations become possible without sacrificing the accuracy of the results. For a brain model having more than 7,000 degrees of freedom, we computed the reaction forces due to indentation with frequency of around 1,000 Hz using a standard dual core PC. Similarly, we conducted simulation of brain shift using a model with more than 50,000 degrees of freedom in less than one minute. The speed benefits of our models result from combining the Total Lagrangian formulation with explicit time integration and low order finite elements.
DOI: 10.1016/j.media.2008.12.001
PubMed: 19152791
Links to Exploration step
pubmed:19152791Le document en format XML
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This requires algorithms that are fast, accurate and can handle material nonlinearities and large deformations. A set of such algorithms is presented in this paper, starting with the finite element formulation and the integration scheme used and addressing common problems such as hourglass control and locking. The computation examples presented prove that by using these algorithms, real time computations become possible without sacrificing the accuracy of the results. For a brain model having more than 7,000 degrees of freedom, we computed the reaction forces due to indentation with frequency of around 1,000 Hz using a standard dual core PC. Similarly, we conducted simulation of brain shift using a model with more than 50,000 degrees of freedom in less than one minute. The speed benefits of our models result from combining the Total Lagrangian formulation with explicit time integration and low order finite elements.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">19152791</PMID><DateCreated><Year>2009</Year><Month>11</Month><Day>02</Day></DateCreated><DateCompleted><Year>2010</Year><Month>02</Month><Day>02</Day></DateCompleted><DateRevised><Year>2014</Year><Month>09</Month><Day>21</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1361-8423</ISSN><JournalIssue CitedMedium="Internet"><Volume>13</Volume><Issue>6</Issue><PubDate><Year>2009</Year><Month>Dec</Month></PubDate></JournalIssue><Title>Medical image analysis</Title><ISOAbbreviation>Med Image Anal</ISOAbbreviation></Journal><ArticleTitle>Suite of finite element algorithms for accurate computation of soft tissue deformation for surgical simulation.</ArticleTitle><Pagination><MedlinePgn>912-9</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.media.2008.12.001</ELocationID><Abstract><AbstractText>Real time computation of soft tissue deformation is important for the use of augmented reality devices and for providing haptic feedback during operation or surgeon training. This requires algorithms that are fast, accurate and can handle material nonlinearities and large deformations. A set of such algorithms is presented in this paper, starting with the finite element formulation and the integration scheme used and addressing common problems such as hourglass control and locking. The computation examples presented prove that by using these algorithms, real time computations become possible without sacrificing the accuracy of the results. For a brain model having more than 7,000 degrees of freedom, we computed the reaction forces due to indentation with frequency of around 1,000 Hz using a standard dual core PC. Similarly, we conducted simulation of brain shift using a model with more than 50,000 degrees of freedom in less than one minute. The speed benefits of our models result from combining the Total Lagrangian formulation with explicit time integration and low order finite elements.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Joldes</LastName><ForeName>Grand Roman</ForeName><Initials>GR</Initials><AffiliationInfo><Affiliation>Intelligent Systems for Medicine Laboratory, School of Mechanical Engineering, The University of Western Australia, 35 Stirling Highway, Crawley/Perth, WA 6009, Australia. grandj@mech.uwa.edu.au</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wittek</LastName><ForeName>Adam</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Miller</LastName><ForeName>Karol</ForeName><Initials>K</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>1-RO3-CA126466-01A1</GrantID><Acronym>CA</Acronym><Agency>NCI NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R03 CA126466</GrantID><Acronym>CA</Acronym><Agency>NCI NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R03 CA126466-01A1</GrantID><Acronym>CA</Acronym><Agency>NCI NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2008</Year><Month>12</Month><Day>24</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Med Image Anal</MedlineTA><NlmUniqueID>9713490</NlmUniqueID><ISSNLinking>1361-8415</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>J Biomech. 2000 Aug;33(8):1005-9</RefSource><PMID 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1997 Nov-Dec;30(11-12):1115-21</RefSource><PMID Version="1">9456379</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D000465">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D000818">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003198">Computer Simulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003238">Connective Tissue</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000033">anatomy & histology</QualifierName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D055119">Elastic Modulus</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D020342">Finite Element Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006801">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D007090">Image Interpretation, Computer-Assisted</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D008953">Models, Anatomic</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D008954">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D012680">Sensitivity and Specificity</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D025321">Surgery, Computer-Assisted</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D014783">Viscosity</DescriptorName></MeshHeading></MeshHeadingList><OtherID 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