Particle based shape regression of open surfaces with applications to developmental neuroimaging

Manasi Datar, Joshua Cates, P. Thomas Fletcher, Sylvain Gouttard, Guido Gerig, Ross Whitaker

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

    Abstract

    Shape regression promises to be an important tool to study the relationship between anatomy and underlying clinical or biological parameters, such as age. In this paper we propose a new method to building shape models that incorporates regression analysis in the process of optimizing correspondences on a set of open surfaces. The statistical significance of the dependence is evaluated using permutation tests designed to estimate the likelihood of achieving the observed statistics under numerous rearrangements of the shape parameters with respect to the explanatory variable. We demonstrate the method on synthetic data and provide a new results on clinical MRI data related to early development of the human head.

    Original languageEnglish (US)
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings
    PublisherSpringer Verlag
    Pages167-174
    Number of pages8
    EditionPART 2
    ISBN (Print)3642042708, 9783642042706
    DOIs
    StatePublished - 2009
    Event12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom
    Duration: Sep 20 2009Sep 24 2009

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume5762 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
    Country/TerritoryUnited Kingdom
    CityLondon
    Period9/20/099/24/09

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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