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)
Year published
1994
Metadata
Show full item recordAbstract
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
Subject
Biological Sciences
Biomedical Engineering
Clinical Sciences
Cognitive Sciences