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dc.contributor.authorHarmouche, Rola
dc.contributor.authorCheriet, Farida
dc.contributor.authorLabelle, Hubert
dc.contributor.authorDansereau, Jean
dc.date.accessioned2015-10-27T17:05:29Z
dc.date.availableNO_RESTRICTIONfr
dc.date.available2015-10-27T17:05:29Z
dc.date.issued2013-03
dc.identifier.urihttp://hdl.handle.net/1866/12511
dc.description.sponsorshipCanadian Institute of Health Research (CIHR)fr
dc.subjectMultimodal image registrationen
dc.subjectInter-patient registrationen
dc.subjectModel to patient registrationen
dc.subjectScoliosisen
dc.subjectScoliosefr
dc.titlePatient-specific model of a scoliotic torso for surgical planningen
dc.typeArticle
dc.contributor.affiliationUniversité de Montréal. Faculté de médecine. Département de chirurgiefr
dc.identifier.doi10.1117/12.2007753
dcterms.abstractA method for the construction of a patient-specific model of a scoliotic torso for surgical planning via inter- patient registration is presented. Magnetic Resonance Images (MRI) of a generic model are registered to surface topography (TP) and X-ray data of a test patient. A partial model is first obtained via thin-plate spline registration between TP and X-ray data of the test patient. The MRIs from the generic model are then fit into the test patient using articulated model registration between the vertebrae of the generic model’s MRIs in prone position and the test patient’s X-rays in standing position. A non-rigid deformation of the soft tissues is performed using a modified thin-plate spline constrained to maintain bone rigidity and to fit in the space between the vertebrae and the surface of the torso. Results show average Dice values of 0.975 ± 0.012 between the MRIs following inter-patient registration and the surface topography of the test patient, which is comparable to the average value of 0.976 ± 0.009 previously obtained following intra-patient registration. The results also show a significant improvement compared to rigid inter-patient registration. Future work includes validating the method on a larger cohort of patients and incorporating soft tissue stiffness constraints. The method developed can be used to obtain a geometric model of a patient including bone structures, soft tissues and the surface of the torso which can be incorporated in a surgical simulator in order to better predict the outcome of scoliosis surgery, even if MRI data cannot be acquired for the patient.en
dcterms.isPartOfurn:ISSN:1996-756X
dcterms.isPartOfurn:ISSN:0277-786X
dcterms.languageengfr
UdeM.VersionRioxxVersion originale de l'auteur·e / Author's Original
oaire.citationTitleProceedings of SPIE
oaire.citationVolume8671


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