Shape index distribution based local surface complexity applied to the human cortex

Sun Hyung Kim, Vladimir Fonov, D. Louis Collins, Guido Gerig, Martin A. Styner

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

    Abstract

    The quantification of local surface complexity in the human cortex has shown to be of interest in investigating population differences as well as developmental changes in neurodegenerative or neurodevelopment diseases. We propose a novel assessment method that represents local complexity as the difference between the observed distributions of local surface topology to its best-fit basic topology model within a given local neighborhood. This distribution difference is estimated via Earth Move Distance (EMD) over the histogram within the local neighborhood of the surface topology quantified via the Shape Index (SI) measure. The EMD scores have a range from simple complexity (0.0), which indicates a consistent local surface topology, up to high complexity (1.0), which indicates a highly variable local surface topology. The basic topology models are categorized as 9 geometric situation modeling situations such as crowns, ridges and fundi of cortical gyro and sulci. We apply a geodesic kernel to calculate the local SI histogram distribution within a given region. In our experiments, we obtained the results of local complexity that shows generally higher complexity in the gyral/sulcal wall regions and lower complexity in some gyral ridges and lowest complexity in sulcal fundus areas. In addition, we show expected, preliminary results of increased surface complexity across most of the cortical surface within the first years of postnatal life, hypothesized to be due to the changes such as development of sulcal pits.

    Original languageEnglish (US)
    Title of host publicationMedical Imaging 2015: Image Processing
    PublisherSPIE
    Volume9413
    ISBN (Print)9781628415032
    DOIs
    StatePublished - 2015
    EventMedical Imaging 2015: Image Processing - Orlando, United States
    Duration: Feb 24 2015Feb 26 2015

    Other

    OtherMedical Imaging 2015: Image Processing
    CountryUnited States
    CityOrlando
    Period2/24/152/26/15

    Fingerprint

    cortexes
    Topology
    topology
    Crowns
    Population
    Earth (planet)
    histograms
    ridges

    Keywords

    • and Earth Move Distance
    • Local Shape Complexity Index
    • Shape Index

    ASJC Scopus subject areas

    • Atomic and Molecular Physics, and Optics
    • Electronic, Optical and Magnetic Materials
    • Biomaterials
    • Radiology Nuclear Medicine and imaging

    Cite this

    Kim, S. H., Fonov, V., Collins, D. L., Gerig, G., & Styner, M. A. (2015). Shape index distribution based local surface complexity applied to the human cortex. In Medical Imaging 2015: Image Processing (Vol. 9413). [941344] SPIE. https://doi.org/10.1117/12.2081560

    Shape index distribution based local surface complexity applied to the human cortex. / Kim, Sun Hyung; Fonov, Vladimir; Collins, D. Louis; Gerig, Guido; Styner, Martin A.

    Medical Imaging 2015: Image Processing. Vol. 9413 SPIE, 2015. 941344.

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

    Kim, SH, Fonov, V, Collins, DL, Gerig, G & Styner, MA 2015, Shape index distribution based local surface complexity applied to the human cortex. in Medical Imaging 2015: Image Processing. vol. 9413, 941344, SPIE, Medical Imaging 2015: Image Processing, Orlando, United States, 2/24/15. https://doi.org/10.1117/12.2081560
    Kim SH, Fonov V, Collins DL, Gerig G, Styner MA. Shape index distribution based local surface complexity applied to the human cortex. In Medical Imaging 2015: Image Processing. Vol. 9413. SPIE. 2015. 941344 https://doi.org/10.1117/12.2081560
    Kim, Sun Hyung ; Fonov, Vladimir ; Collins, D. Louis ; Gerig, Guido ; Styner, Martin A. / Shape index distribution based local surface complexity applied to the human cortex. Medical Imaging 2015: Image Processing. Vol. 9413 SPIE, 2015.
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