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Nonparametric joint shape learning for customized shape modeling

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Ünal, Gözde (2010) Nonparametric joint shape learning for customized shape modeling. Computerized Medical Imaging and Graphics, 34 (4). pp. 298-307. ISSN 0895-6111

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Abstract

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.
Item Type: Article
Uncontrolled Keywords: Shape estimation; Variational shape optimization; Customized shape modeling; Nonparametric shape density; Joint shape prior; Hearing aid design; Pre-operative and intra-operative shape modeling
Subjects: Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Gözde Ünal
Date Deposited: 06 May 2010 10:55
Last Modified: 26 Apr 2022 08:36
URI: https://research.sabanciuniv.edu/id/eprint/13912

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