TY - JOUR
T1 - Nonparametric joint shape learning for customized shape modeling
AU - Unal, Gozde
PY - 2010/6
Y1 - 2010/6
N2 - 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.
AB - 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.
KW - Customized shape modeling
KW - Hearing aid design
KW - Joint shape prior
KW - Nonparametric shape density
KW - Pre-operative and intra-operative shape modeling
KW - Shape estimation
KW - Variational shape optimization
UR - https://www.scopus.com/pages/publications/77952239113
U2 - 10.1016/j.compmedimag.2009.12.001
DO - 10.1016/j.compmedimag.2009.12.001
M3 - Article
C2 - 20044237
AN - SCOPUS:77952239113
SN - 0895-6111
VL - 34
SP - 298
EP - 307
JO - Computerized Medical Imaging and Graphics
JF - Computerized Medical Imaging and Graphics
IS - 4
ER -