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

  • Hildur Ólafsdóttir
  • Michael Sass Hansen
  • Karl Sjöstrand
  • Tron A. Darvann
  • Nuno V. Hermann
  • Estanislao Oubel
  • Bjarne K. Ersbøll
  • Rasmus Larsen
  • Alejandro F. Frangi
  • Per Larsen
  • Chad A. Perlyn
  • Gillian M. Morriss-Kay
  • Sven Kreiborg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)

Abstract

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 craniofacial 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. The results show that SPCA outperforms both ICA and PCA with respect to the Fisher discriminant, although many similarities are found with respect to ICA.

Keywords

Independent Component Analysis Nonrigid Registration Cranial Suture Temporal Subtraction Crouzon Syndrome 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Hildur Ólafsdóttir
    • 1
    • 2
  • Michael Sass Hansen
    • 1
  • Karl Sjöstrand
    • 1
  • Tron A. Darvann
    • 2
  • Nuno V. Hermann
    • 2
    • 3
  • Estanislao Oubel
    • 4
  • Bjarne K. Ersbøll
    • 1
  • Rasmus Larsen
    • 1
  • Alejandro F. Frangi
    • 4
  • Per Larsen
    • 2
  • Chad A. Perlyn
    • 5
  • Gillian M. Morriss-Kay
    • 6
  • Sven Kreiborg
    • 2
    • 3
    • 7
  1. 1.Informatics and Mathematical Modelling, Technical University of Denmark, LyngbyDenmark
  2. 2.3D-Laboratory, School of Dentistry, University of Copenhagen; Copenhagen University Hospital; Informatics and Mathematical Modelling, Technical University of Denmark, CopenhagenDenmark
  3. 3.Department of Pediatric Dentistry and Clinical Genetics, School of Dentistry, Faculty of Health Sciences, University of Copenhagen, CopenhagenDenmark
  4. 4.Computational Imaging Lab, Department of Technology - D.326, Pompeu Fabra University, BarcelonaSpain
  5. 5.Division of Plastic Surgery, Washington University School of Medicine, St. Louis, MOUSA
  6. 6.Department of Physiology, Anatomy and Genetics, Oxford University, OxfordUK
  7. 7.Department of Clinical Genetics, The Juliane Marie Centre, Copenhagen University Hospital, CopenhagenDenmark

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