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Nonparametric Joint Shape Learning for Customized Shape Modeling
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Institution: |
Sabanci University, Faculty of Engineering and Natural Sciences, Tuzla 34956, Istanbul, Turkey. gozdeunal@sabanciuniv.edu |
Publisher: |
Elsevier Science |
Publication Date: |
Jun-2010 |
Journal: |
Comput Med Imaging Graph |
Volume Number: |
34 |
Issue Number: |
4 |
Pages: |
298-307 |
Citation: |
Comput Med Imaging Graph. 2010 Jun;34(4):298-307. |
PubMed ID: |
20044237 |
PMCID: |
PMC2972425 |
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 |
Appears in Collections: |
NCIGT |
Sponsors: |
U41 RR019703 (RR) funded by NCRR NIH HHS |
Generated Citation: |
Unal G. Nonparametric Joint Shape Learning for Customized Shape Modeling. Comput Med Imaging Graph. 2010 Jun;34(4):298-307. PMID: 20044237. PMCID: PMC2972425. |
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| Paper: | Download, View online |
| Export citation: |
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.
Additional Material
1 File (92.299kB)
Unal-CompMedImagingGraphics2010-fig12.jpg (92.299kB)