Sparse Statistical Deformation Model for the Analysis of Craniofacial Malformations in the Crouzon Mouse

Hildur Ólafsdóttir, Michael Sass Hansen, Karl Sjöstrand, Tron Andre Darvann, Nuno V. Hermann, Estanislao Oubel, Bjarne Kjær Ersbøll, Rasmus Larsen, Alejandro F. Frangi, Per Larsen, Chad A. Perlynn, Gillian M. Morriss-Kay, Sven Kreiborg, Bjarne Kjær Ersbøll (Editor), Janne Heikkilä (Editor), Ivar Austvoll, Ingela Nyström (Editor)

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


    Crouzon syndrome is characterised by the premature fusion of cranial sutures. Recently the first 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 different 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.
    Original languageEnglish
    Title of host publicationScandinavian Conference on Image Analysis 2007
    Publication date2007
    Publication statusPublished - 2007
    Event15th Scandinavian Conference on Image Analysis - Aalborg, Denmark
    Duration: 10 Jun 200724 Jun 2007
    Conference number: 15


    Conference15th Scandinavian Conference on Image Analysis


    • Sparse PCA
    • statistical deformation model
    • Crouzon syndrome


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