Sparse Statistical Deformation Model for the Analysis of Craniofacial Malformations in the Crouzon Mouse |
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| Abstract | Crouzon syndrome is characterised by the premature fusion
of cranial sutures. Recently the rst genetic Crouzon mouse model was
generated. In this study, Micro CT skull scannings of wild-type mice and
Crouzon mice were investigated. Using nonrigid registration, a wild-type
mouse atlas was built. The atlas was registered to all mice providing
parameters controlling the deformations for each subject. Our previous
PCA-based statistical deformation model on these parameters revealed
only one discriminating mode of variation. Aiming at distributing the
discriminating variation over more modes we built a di erent model using
Independent Component Analysis (ICA). Here, we focus on a third
method, sparse PCA (SPCA), which aims at approximating the properties
of a standard PCA while introducing sparse modes of variation.
This approach is compared to a standard PCA and ICA. The results
show that the SPCA outperforms both ICA and PCA with respect to
the Fisher discriminant. |
| Keywords | Sparse PCA, statistical deformation model, Crouzon syndrome |
| Type | Conference paper [With referee] |
| Conference | Scandinavian Conference on Image Analysis 2007 |
| Editors | |
| Year | 2007 |
| Publisher | Springer |
| Series | Lecture notes in computer science (LNCS) |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics |