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dc.contributor.authorCourchesne, Olivier
dc.contributor.authorGuibault, François
dc.contributor.authorParent, Stefan
dc.contributor.authorCheriet, Farida
dc.date.accessioned2016-02-16T16:17:16Z
dc.date.availableMONTHS_WITHHELD:12fr
dc.date.available2016-02-16T16:17:16Z
dc.date.issued2015-01-09
dc.identifier.urihttp://hdl.handle.net/1866/13065
dc.description.sponsorshipNatural Sciences and Engineering Research Council (NSERC) of Canada and the MEDITIS training program (´Ecole Polytechnique de Montreal and NSERC).fr
dc.subjectPatient-specificfr
dc.subjectTraitement d'image par ordinateurfr
dc.subjectMagnetic resonance imaging (MRI)en
dc.subjectImagerie par résonance magnétiquefr
dc.subject3D geometric modelen
dc.subjectAdaptive mesh refinement (AMR)en
dc.subjectAlgorithmesfr
dc.subjectRaffinement adaptatif de maillagefr
dc.titlePatient-specific anisotropic model of human trunk based on MR datafr
dc.typeArticlefr
dc.contributor.affiliationUniversité de Montréal. Faculté de médecine. Département de chirurgiefr
dc.identifier.doi10.1002/cnm.2724
dcterms.abstractThere are many ways to generate geometrical models for numerical simulation, and most of them start with a segmentation step to extract the boundaries of the regions of interest. This paper presents an algorithm to generate a patient-specific three-dimensional geometric model, based on a tetrahedral mesh, without an initial extraction of contours from the volumetric data. Using the information directly available in the data, such as gray levels, we built a metric to drive a mesh adaptation process. The metric is used to specify the size and orientation of the tetrahedral elements everywhere in the mesh. Our method, which produces anisotropic meshes, gives good results with synthetic and real MRI data. The resulting model quality has been evaluated qualitatively and quantitatively by comparing it with an analytical solution and with a segmentation made by an expert. Results show that our method gives, in 90% of the cases, as good or better meshes as a similar isotropic method, based on the accuracy of the volume reconstruction for a given mesh size. Moreover, a comparison of the Hausdorff distances between adapted meshes of both methods and ground-truth volumes shows that our method decreases reconstruction errors faster. Copyright © 2015 John Wiley & Sons, Ltd.fr
dcterms.languageengfr
UdeM.VersionRioxxVersion acceptée / Accepted Manuscript
oaire.citationTitleInternational journal for numerical methods in biomedical engineering
oaire.citationVolume31
oaire.citationIssue9


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