Image reconstruction by minimizing second-order moment.

K H Park; S B Park

doi:10.1177/016173469001200201

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Image reconstruction by minimizing second-order moment.

K H Park·S B Park

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Abstract

Statistical methods have received much attention in image reconstruction, especially when the projection data are not sufficient in number, since they usually give more reliable results in such a case than other methods. In this paper, we propose a new statistical method which minimizes the second-order moment of an object that indicates the variance and randomness in a statistical structure. By minimizing the second-order moment, the resulting image reflects the statistical structure imposed by the available information and is biased toward a flat gray structure in the absence of information. The computer simulation results show a good convergence behavior of the proposed method. This method was successfully applied to ultrasound attenuation CT using a sponge phantom.

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Algorithms Bayes Theorem Computer Simulation Humans Image Processing, Computer-Assisted Models, Statistical Tomography, X-Ray Computed Ultrasonics Journal Article

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K H Park, S B Park. 1990. Image reconstruction by minimizing second-order moment.. https://doi.org/10.1177/016173469001200201

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