Statistics of pose and shape in multi-object complexes using principal geodesic analysis

Martin Styner, Kevin Gorczowski, Tom Fletcher, Ja Yeon Jeong, Stephen M. Pizer, Guido Gerig

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    A main focus of statistical shape analysis is the description of variability of a population of geometric objects. In this paper, we present work in progress towards modeling the shape and pose variability of sets of multiple objects. Principal geodesic analysis (PGA) is the extension of the standard technique of principal component analysis (PCA) into the nonlinear Riemannian symmetric space of pose and our medial m-rep shape description, a space in which use of PCA would be incorrect. In this paper, we discuss the decoupling of pose and shape in multi-object sets using different normalization settings. Further, we introduce new methods of describing the statistics of object pose using a novel extension of PGA, which previously has been used for global shape statistics. These new pose statistics are then combined with shape statistics to form a more complete description of multi-object complexes. We demonstrate our methods in an application to a longitudinal pediatric autism study with object sets of 10 subcortical structures in a population of 20 subjects. The results show that global scale accounts for most of the major mode of variation across time. Furthermore, the PGA components and the corresponding distribution of different subject groups vary significantly depending on the choice of normalization, which illustrates the importance of global and local pose alignment in multi-object shape analysis.

    Original languageEnglish (US)
    Title of host publicationMedical Imaging and Augmented Reality - Third International Workshop
    PublisherSpringer Verlag
    Pages1-8
    Number of pages8
    ISBN (Print)3540372202, 9783540372202
    DOIs
    StatePublished - 2006
    Event3rd International Workshop on Medical Imaging and Augmented Reality - Shanghai, China
    Duration: Aug 17 2006Aug 18 2006

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume4091 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other3rd International Workshop on Medical Imaging and Augmented Reality
    CountryChina
    CityShanghai
    Period8/17/068/18/06

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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