Statistical shape analysis of neuroanatomical structures based on medial models

Martin Styner, G. Gerig, J. Lieberman, D. Jones, D. Weinberger

    Research output: Contribution to journalArticle

    Abstract

    Knowledge about the biological variability of anatomical objects is essential for statistical shape analysis and discrimination between healthy and pathological structures. This paper describes a novel approach that incorporates the variability of an object population into the generation of a characteristic 3D shape model. The proposed shape representation is a coarse-scale sampled medial description derived from a fine-scale spherical harmonics (SPHARM) boundary description. This medial description is composed of a net of medial samples (m-rep) with fixed graph properties. The medial model is computed automatically from a predefined shape space using pruned 3D Voronoi skeletons. A new method determines the stable medial branching topology from the shape space. An intrinsic coordinate system and an implicit correspondence between shapes is defined on the medial manifold. Several studies of biological structures clearly demonstrate that the novel representation has the promise to describe shape changes in a natural and intuitive way. A new medial shape similarity study of group differences between monozygotic and dizygotic twins in lateral ventricle shape demonstrates the meaningful and powerful representation of local and global form.

    Original languageEnglish (US)
    Pages (from-to)207-220
    Number of pages14
    JournalMedical Image Analysis
    Volume7
    Issue number3
    DOIs
    StatePublished - Sep 2003

    Keywords

    • Brain morphometry
    • Medial shape description
    • Medical image analysis
    • Shape analysis
    • Voronoi skeleton

    ASJC Scopus subject areas

    • Radiological and Ultrasound Technology
    • Radiology Nuclear Medicine and imaging
    • Computer Vision and Pattern Recognition
    • Health Informatics
    • Computer Graphics and Computer-Aided Design

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