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pubmed-article:20044237pubmed:abstractTextWe present a shape optimization approach to compute patient-specific models in customized prototyping applications. We design a coupled shape prior to model the transformation between a related pair of surfaces, using a nonparametric joint probability density estimation. The coupled shape prior forces with the help of application-specific data forces and smoothness forces drive a surface deformation towards a desired output surface. We demonstrate the usefulness of the method for generating customized shape models in applications of hearing aid design and pre-operative to intra-operative anatomic surface estimation.lld:pubmed
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pubmed-article:20044237pubmed:issn1879-0771lld:pubmed
pubmed-article:20044237pubmed:authorpubmed-author:UnalGozdeGlld:pubmed
pubmed-article:20044237pubmed:copyrightInfoCopyright 2009 Elsevier Ltd. All rights reserved.lld:pubmed
pubmed-article:20044237pubmed:issnTypeElectroniclld:pubmed
pubmed-article:20044237pubmed:volume34lld:pubmed
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pubmed-article:20044237pubmed:pagination298-307lld:pubmed
pubmed-article:20044237pubmed:dateRevised2010-12-3lld:pubmed
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pubmed-article:20044237pubmed:year2010lld:pubmed
pubmed-article:20044237pubmed:articleTitleNonparametric joint shape learning for customized shape modeling.lld:pubmed
pubmed-article:20044237pubmed:affiliationSabanci University, Faculty of Engineering and Natural Sciences, Tuzla 34956, Istanbul, Turkey. gozdeunal@sabanciuniv.edulld:pubmed
pubmed-article:20044237pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:20044237pubmed:publicationTypeResearch Support, N.I.H., Extramurallld:pubmed