Models of Normal Variation and Local Contrasts in Hippocampal Anatomy

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5242)


We develop a model of continuous spherical shapes and use it to analyze the anatomy of the hippocampus. To account for the geometry of bends and folds, the model relies on a geodesic metric that is sensitive to first-order deformations. We construct an atlas of the hippocampus as a mean shape and develop statistical models to characterize quantitative and qualitative normal shape variation. We also develop a localization tool to identify local contrasts in the anatomy of different populations. The tool is applied to the detection, characterization and visualization of anatomical differences such as local enlargement and gains in volume on the right hippocampus of blind subjects.


Singular Value Decomposition Shape Variation Geodesic Distance Shape Space Local Contrast 
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.


  1. 1.
    Kendall, D.G.: Shape manifolds, Procrustean metrics and complex projective spaces. Bulletin of London Mathematical Society 16, 81–121 (1984)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Huckemann, S., Ziezold, H.: Principal component analysis for Riemannian manifolds, with an application to triangular shape spaces. Advances in Applied Probability 38, 299–319 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Dryden, I.L., Mardia, K.V.: Statistical Shape Analysis. John Wiley & Son, Chichester (1998)zbMATHGoogle Scholar
  4. 4.
    Shi, Y., Thompson, P., Zubicaray, G., Ross, S., Tu, Z., Dinov, I., Toga, A.: Direct mapping of hippocampal surfaces with intrinsic shape context. Neuro Image 36(3), 792–807 (2007)Google Scholar
  5. 5.
    Praun, E., Hoppe, H.: Spherical parametrization and remeshing. In: ACM SIGGRAPH 2003, pp. 340–349 (2003)Google Scholar
  6. 6.
    Liu, X., Bowers, J., Mio, W.: Parametrization, alignment and shape of spherical surfaces. In: 2nd International Conference on Computer Vision Theory and Applications (VISAPP), vol. 1, pp. 199–206 (2007)Google Scholar
  7. 7.
    Voss, P., Lassonde, M., Gougoux, F., Fortin, M., Guillemot, J.P., Lepore, F.: Early- and late-onset blind individuals show supra-normal auditory abilities in far-space. Current Biology 14(19), 1734–1738 (2004)CrossRefGoogle Scholar
  8. 8.
    Wang, L., Miller, J., Gado, M., Mckeel, D., Rothermich, M., Miller, M., Morris, J., Csernansky, J.: Abnormalities of hippocampal surface structure on very mild dementia of the alzheimer type. Neuro Image 30(1), 52–60 (2006)Google Scholar
  9. 9.
    Gerig, G., Styner, M., Jones, D., Weinberger, D., Lieberman, J.: Shape analysis of brain ventricles using SPHARM. In: Proc. of MMBIA, pp. 171–178 (2001)Google Scholar
  10. 10.
    Styner, M., Gerig, G., Lieberman, J., Jones, D., Weinberger, D.: Statistical shape analysis of neuroanatomical structures based on medial models. Med. Image Anal. 7(3), 207–220 (2003)CrossRefGoogle Scholar
  11. 11.
    Pizer, S., Fritsch, D., Yushkevich, P., Johnson, V., Chaney, E.: Segmentation, registration and measurement of shape variation via image object shape. IEEE Trans. Med. Imag. 18(10), 851–865 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  1. 1.Department of MathematicsFlorida State UniversityTallahasseeUSA
  2. 2.Laboratory of Neuro ImagingUCLA School of MedicineLos AngelesUSA
  3. 3.Department of Computer ScienceFlorida State UniversityTallahasseeUSA
  4. 4.Departement de PsychologieUniversité de MontréalMontréalCanada

Personalised recommendations