Topology preserving atlas construction from shape data without correspondence using sparse parameters

Stanley Durrleman, Marcel Prastawa, Julie R. Korenberg, Sarang Joshi, Alain Trouvé, Guido Gerig

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

    Abstract

    Statistical analysis of shapes, performed by constructing an atlas composed of an average model of shapes within a population and associated deformation maps, is a fundamental aspect of medical imaging studies. Usual methods for constructing a shape atlas require point correspondences across subjects, which are difficult in practice. By contrast, methods based on currents do not require correspondence. However, existing atlas construction methods using currents suffer from two limitations. First, the template current is not in the form of a topologically correct mesh, which makes direct analysis on shapes difficult. Second, the deformations are parametrized by vectors at the same location as the normals of the template current which often provides a parametrization that is more dense than required. In this paper, we propose a novel method for constructing shape atlases using currents where topology of the template is preserved and deformation parameters are optimized independently of the shape parameters. We use an L1 -type prior that enables us to adaptively compute sparse and low dimensional parameterization of deformations. We show an application of our method for comparing anatomical shapes of patients with Down’s syndrome and healthy controls, where the sparse parametrization of diffeomorphisms decreases the parameter dimension by one order of magnitude.

    Original languageEnglish (US)
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings
    EditorsNicholas Ayache, Herve Delingette, Polina Golland, Kensaku Mori
    PublisherSpringer Verlag
    Pages223-230
    Number of pages8
    ISBN (Print)9783642334535
    DOIs
    StatePublished - 2012
    Event15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012 - Nice, France
    Duration: Oct 1 2012Oct 5 2012

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume7512 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012
    CountryFrance
    CityNice
    Period10/1/1210/5/12

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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