Effects of Manufacturing Variability on Model-Based CT Image Reconstruction
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Begun in 1973, the Review of Progress in Quantitative Nondestructive Evaluation (QNDE) is the premier international NDE meeting designed to provide an interface between research and early engineering through the presentation of current ideas and results focused on facilitating a rapid transfer to engineering development.
This site provides free, public access to papers presented at the annual QNDE conference between 1983 and 1999, and abstracts for papers presented at the conference since 2001.
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Abstract
In recent years, x-ray Computed Tomography (CT) imaging has become much more widely used in industrial applications. In many such applications, however, only incomplete data sets [1] are available, and image quality is degraded by the absence of complete data. In this paper, a model-based CT reconstruction technique for enhancing incomplete data CT image quality is presented. A two-dimensional registration method which will ensure proper utilization of a priori information from CAD model is introduced. Images are shown to demonstrate manipulator position variability as well as blade to blade variability. Variability is quantified by the translation and rotation factors used in geometric transformation. In addition, incomplete data CT image simulation results are presented which show the effects of manufacturing variability on flaw detectability in these images.