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  • 3D autocorrelation for the determination of large pore sizes

    Author(s)
    Lucas, A. J.
    Derbyshire, J. A.
    Dillon, N.
    Peyron, M.
    Pierens, Gregory
    Hall, L. D.
    Phelps, D. W.
    Stewart, R. C.
    Griffith University Author(s)
    Pierens, Gregory K.
    Year published
    1994
    Metadata
    Show full item record
    Abstract
    A data analysis methodology is used to process 3D NMR image data acquired for porous systems. The method extracts the mean size of those repeating elements in the image data which are large compared with the image voxel dimensions. In this work we extend the two-dimensional (2D) image analysis method described by others to three spatial dimensions (3D). 3D image data were acquired at a magnetic field strength of 7 T using NMR microscopy hardware. The 3D autocorrelation function obtained from the data reveals a characteristic pore size in each dimension.A data analysis methodology is used to process 3D NMR image data acquired for porous systems. The method extracts the mean size of those repeating elements in the image data which are large compared with the image voxel dimensions. In this work we extend the two-dimensional (2D) image analysis method described by others to three spatial dimensions (3D). 3D image data were acquired at a magnetic field strength of 7 T using NMR microscopy hardware. The 3D autocorrelation function obtained from the data reveals a characteristic pore size in each dimension.
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    Journal Title
    Magnetic Resonance Imaging
    Volume
    12
    Issue
    2
    DOI
    https://doi.org/10.1016/0730-725X(94)91530-X
    Subject
    Biological Sciences
    Biomedical Engineering
    Clinical Sciences
    Cognitive Sciences
    Publication URI
    http://hdl.handle.net/10072/123340
    Collection
    • Journal articles

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