Correction scheme for multiple correlated statistical tests in local shape analysis

Martin Styner, Guido Gerig

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

    Abstract

    In neuroimaging research shape analysis has become a field of great interest due to the ability to locate morpho-logical brain changes between different groups. Currently, many local shape analysis approaches fail to correct for their high number of correlated statistical tests. This can result in an overly optimistic estimate of the local shape analysis. This paper presents a correction scheme for objects described by the parametrized 3D closed surface description SPHARM. The SPHARM parameterization was determined via area preserving, minimal distortion optimization. The correction scheme decomposes the object surface into overlapping planar images via a cylindrical equal area projection of the parameterization. The images are individually analyzed with the SnPM/SPM package using a voxel-level non-parametric multiple testing procedure based on permutation tests. The correction scheme employs conservative tests resulting in a pessimistic estimate. We present an application of the correction scheme to the shape similarity analysis of lateral ventricles.

    Original languageEnglish (US)
    Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
    EditorsJ.M. Fitzpatrick, M. Sonka
    Pages233-240
    Number of pages8
    Volume5370 I
    DOIs
    StatePublished - 2004
    EventProgress in Biomedical Optics and Imaging - Medical Imaging 2004: Imaging Processing - San Diego, CA, United States
    Duration: Feb 16 2004Feb 19 2004

    Other

    OtherProgress in Biomedical Optics and Imaging - Medical Imaging 2004: Imaging Processing
    Country/TerritoryUnited States
    CitySan Diego, CA
    Period2/16/042/19/04

    Keywords

    • Multiple comparison problem
    • Shape analysis
    • Statistical non-parametric tests

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Condensed Matter Physics

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