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Abstract

A method is presented for interpreting the values of x-ray attenuation coefficients reconstructed in computed tomography of porous media, while overcoming the ambiguity caused by the multichromatic nature of x-rays, dilution by void, and material heterogeneity. The method enables determination of porosity without relying on calibration or image segmentation or thresholding to discriminate pores from solid material. It distinguishes between solution-accessible and inaccessible pores, and provides the spatial and frequency distributions of solid-matrix material in a heterogeneous medium. This is accomplished by matching an image of a sample saturated with a contrast solution with that saturated with a transparent solution. Voxels occupied with solid-material and inaccessible pores are identified by the fact that they maintain the same location and image attributes in both images, with voxels containing inaccessible pores appearing empty in both images. Fully porous and accessible voxels exhibit the maximum contrast, while the rest are porous voxels containing mixtures of pore solutions and solid. This matching process is performed with an image registration computer code, and image processing software that requires only simple subtraction and multiplication (scaling) processes. The process is demonstrated in dolomite (non-uniform void distribution, homogeneous solid matrix) and sandstone (nearly uniform void distribution, heterogeneous solid matrix) samples, and its overall performance is shown to compare favorably with a method based on calibration and thresholding.

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... In the area of the measuring method and the field of micro tomogra-92 phy, the reader is referred to the work of Miller et al. [14][15][16] and Lin 93 et al. [17][18][19][20][21] for particulate systems. In the field of analysis of micro-94 tomography measurements of porous media, many works have 95 emerged in recent years [18,[22][23][24][25][26]. The authors deal with the perme-96 ability and pore size distributions on which many modeling approaches 97 are based. ...
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Partial volume blurring precludes accurate measurement of structural dimensions in the limited-resolution regime in which image voxel size is larger than the typical structural element to be resolved. Since acquiring images at increased resolution often exacts an unacceptable signal-to-noise ratio (SNR) penalty, methods to alleviate the adverse effects of partial volume blurring are instrumental for the accurate measurement of architectural parameters in applications such as predicting the mechanical competence of trabecular bone networks. In the current work, a novel post-processing method, referred to as "subvoxel processing," is described for increasing apparent image resolution. The method is applicable to volumes of interest containing material phases of two discrete signal intensities. The principal strategy consists of subdividing voxels and assigning voxel intensities to each subvoxel on the basis of local neighborhood criteria and strict mass conservation. In the current work, the method's accuracy has been evaluated using microcomputed tomography images (22 x 22 x 22 microm(3) voxel size) of human trabecular bone. The results demonstrate that subvoxel processing is significantly more accurate than trilinear interpolation in decreasing apparent voxel size, especially in the presence of noise. In addition, the method's effectiveness is illustrated with MR images of human trabecular bone acquired in vivo at 137 x 137 x 350 microm(3) voxel size. The subvoxel-processed images are shown to have architectural features characteristic of images acquired at higher spatial resolution.
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In vitro testing of bone cement has historically resulted in the belief that porosity should be minimised to help reduce the risk of prosthesis failure through aseptic loosening. Traditional porosity measurement techniques rely on the analysis of a two dimensional representation of a three dimensional structure. However, with an increasing interest in the number, size and distribution of pores in bone cement, the reliability of a two dimensional approach is questionable. The purpose of this study was to investigate the use of micro computed tomography (micro-CT) for the three dimensional measurement of bone cement porosity by comparison with two traditional techniques. Eighteen bone cement specimens were analysed for porosity using each technique. Levels of agreement between techniques were evaluated, and technique precision was assessed in terms of repeatability and sensitivity to changes in threshold. Micro-CT data was used to illustrate the effectiveness of predicting the porosity of a whole structure from a sample region; an approach often used with traditional techniques. In summary, poor agreement was found between all techniques. However, micro-CT was found to be significantly more repeatable and less sensitive to changes in threshold. The results demonstrated that porosity cannot be reliably determined using traditional techniques and that a large proportion of a specimen is required to provide an accurate porosity measurement.
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A single volume element (voxel) in a medical image may be composed of a mixture of multiple tissue types. The authors call voxels which contain multiple tissue classes mixels. A statistical mixel image model based on Markov random field (MRF) theory and an algorithm for the classification of mixels are presented. The authors concentrate on the classification of multichannel magnetic resonance (MR) images of the brain although the algorithm has other applications. The authors also present a method for compensating for the gray-level variation of MR images between different slices, which is primarily caused by the inhomogeneity of the RF field produced by the imaging coil
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