Optimal Processing of Computed Tomography Images Using Experimentally Measured Noise Properties

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Abstract
The spatial resolution and noise properties of a computed tomography (CT) image may be altered by 2-dimensional linear filtering of the initial image. Filters are derived that minimize the noise variance subject to a constraint on the spatial resolution. The resulting filter functions can reduce the noise variance by 17% in comparison with conventional filters. The method for obtaining these filters requires knowledge of the noise and imaging properties of the system. Theoretical expressions for these properties are derived and experimental techniques for their measurement introduced. The statistical characteristics are anisotropic, spatially variant and object dependent. The implications of this result for optimal filtering and for the general problem of CT image noise property measurement are discussed.

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