Cortical surface-based construction of individual structural network with application to early brain development study

Yu Meng, Gang Li, Weili Lin, John H. Gilmore, Dinggang Shen

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

    2 Citations (Scopus)

    Abstract

    Analysis of anatomical covariance for cortex morphology in individual subjects plays an important role in the study of human brains. However, the approaches for constructing individual structural networks have not been well developed yet. Existing methods based on patch-wise image intensity similarity suffer from several major drawbacks, i.e., 1) violation of cortical topological properties, 2) sensitivity to intensity heterogeneity, and 3) influence by patch size heterogeneity. To overcome these limitations, this paper presents a novel cortical surface-based method for constructing individual structural networks. Specifically, our method first maps the cortical surfaces onto a standard spherical surface atlas and then uniformly samples vertices on the spherical surface as the nodes of the networks. The similarity between any two nodes is computed based on the biologically-meaningful cortical attributes (e.g., cortical thickness) in the spherical neighborhood of their sampled vertices. The connection between any two nodes is established only if the similarity is larger than a user-specified threshold. Through leveraging spherical cortical surface patches, our method generates biologically-meaningful individual networks that are comparable across ages and subjects. The proposed method has been applied to construct cortical-thickness networks for 73 healthy infants, with each infant having two MRI scans at 0 and 1 year of age. The constructed networks during the two ages were compared using various network metrics, such as degree, clustering coefficient, shortest path length, small world property, global efficiency, and local efficiency. Experimental results demonstrate that our method can effectively construct individual structural networks and reveal meaningful patterns in early brain development.

    Original languageEnglish
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings
    EditorsAlejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells
    PublisherSpringer Verlag
    Pages560-568
    Number of pages9
    ISBN (Print)9783319245737
    DOIs
    Publication statusPublished - 2015
    Event18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany
    Duration: 2015 Oct 52015 Oct 9

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9351
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
    Country/TerritoryGermany
    CityMunich
    Period15/10/515/10/9

    Bibliographical note

    Publisher Copyright:
    © Springer International Publishing Switzerland 2015.

    Keywords

    • Cortical thickness
    • Development
    • Individual networks
    • Infant

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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