pubmed-article:20044237 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:20044237 | lifeskim:mentions | umls-concept:C0023185 | lld:lifeskim |
pubmed-article:20044237 | lifeskim:mentions | umls-concept:C0022417 | lld:lifeskim |
pubmed-article:20044237 | lifeskim:mentions | umls-concept:C0332479 | lld:lifeskim |
pubmed-article:20044237 | lifeskim:mentions | umls-concept:C0870071 | lld:lifeskim |
pubmed-article:20044237 | lifeskim:mentions | umls-concept:C1880202 | lld:lifeskim |
pubmed-article:20044237 | pubmed:issue | 4 | lld:pubmed |
pubmed-article:20044237 | pubmed:dateCreated | 2010-4-26 | lld:pubmed |
pubmed-article:20044237 | pubmed:abstractText | We 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 |
pubmed-article:20044237 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:20044237 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:20044237 | pubmed:language | eng | lld:pubmed |
pubmed-article:20044237 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:20044237 | pubmed:citationSubset | IM | lld:pubmed |
pubmed-article:20044237 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:20044237 | pubmed:month | Jun | lld:pubmed |
pubmed-article:20044237 | pubmed:issn | 1879-0771 | lld:pubmed |
pubmed-article:20044237 | pubmed:author | pubmed-author:UnalGozdeG | lld:pubmed |
pubmed-article:20044237 | pubmed:copyrightInfo | Copyright 2009 Elsevier Ltd. All rights reserved. | lld:pubmed |
pubmed-article:20044237 | pubmed:issnType | Electronic | lld:pubmed |
pubmed-article:20044237 | pubmed:volume | 34 | lld:pubmed |
pubmed-article:20044237 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:20044237 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:20044237 | pubmed:pagination | 298-307 | lld:pubmed |
pubmed-article:20044237 | pubmed:dateRevised | 2010-12-3 | lld:pubmed |
pubmed-article:20044237 | pubmed:meshHeading | pubmed-meshheading:20044237... | lld:pubmed |
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pubmed-article:20044237 | pubmed:meshHeading | pubmed-meshheading:20044237... | lld:pubmed |
pubmed-article:20044237 | pubmed:year | 2010 | lld:pubmed |
pubmed-article:20044237 | pubmed:articleTitle | Nonparametric joint shape learning for customized shape modeling. | lld:pubmed |
pubmed-article:20044237 | pubmed:affiliation | Sabanci University, Faculty of Engineering and Natural Sciences, Tuzla 34956, Istanbul, Turkey. gozdeunal@sabanciuniv.edu | lld:pubmed |
pubmed-article:20044237 | pubmed:publicationType | Journal Article | lld:pubmed |
pubmed-article:20044237 | pubmed:publicationType | Research Support, N.I.H., Extramural | lld:pubmed |