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GeoSP: A parallel method for a cortical surface parcellation based on geodesic distance.

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    Summary
    This summary is machine-generated.

    GeoSP is a new parallel method for cortical parcellation using geodesic distance. It creates more homogeneous brain parcels compared to existing atlases, improving structural connectivity analysis.

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    Area of Science:

    • Neuroimaging
    • Computational Neuroscience
    • Brain Mapping

    Background:

    • Accurate parcellation of the human cortex is crucial for understanding brain function and connectivity.
    • Existing atlases like Desikan-Killiany and Destrieux have limitations in capturing cortical topology.
    • There is a need for data-driven methods that generate homogeneous and reproducible cortical parcels.

    Purpose of the Study:

    • To introduce GeoSP, a novel parallel method for cortical parcellation based on geodesic distance.
    • To evaluate the homogeneity and efficiency of GeoSP compared to established atlases.
    • To provide a tool for data-driven cortical parcellation and analysis.

    Main Methods:

    • GeoSP represents the cortical mesh as a graph and employs parallel K-means clustering.
    • The method offers two modes: parcellation based on the Desikan-Killiany atlas and complete cortex parcellation.
    • The algorithm considers gyri and sulci topology using geodesic distances.

    Main Results:

    • Both GeoSP modes produced homogeneous sub-parcels across different parcellation numbers.
    • Execution times were efficient: 18s for Desikan-Killiany subdivision and 82s for whole cortex parcellation (350 sub-parcels).
    • Comparison with Desikan-Killiany and Destrieux atlases in 50 subjects showed GeoSP parcels were more homogeneous and structural connectivity was reproducible.

    Conclusions:

    • GeoSP offers a robust and efficient method for creating homogeneous cortical parcellations.
    • The method improves upon existing atlases in terms of parcel homogeneity and structural connectivity reproducibility.
    • GeoSP will be a valuable tool for the neuroscience community for evaluating data-driven cortical parcellations.