X-ray computed tomography (XCT) enables the dimensional measurement and inspection of highly geometrically complex engineering components that are unmeasurable using optical and tactile instruments. Conventional XCT scans use a circular scan trajectory where X-ray projections are acquired with a uniform angular spacing; this approach treats all projections as being of equal importance, in practice, some projections contain more object information than others. In this work we capitalize on this concept by intelligently selecting projections with a view to improve the quality of surface models extracted from an XCT data-set.
View Article and Find Full Text PDFLab-based X-ray computed tomography (XCT) systems use X-ray sources that emit a polychromatic X-ray spectrum and detectors that do not detect all X-ray photons with the same efficiency. A consequence of using a polychromatic X-ray source is that beam hardening artefacts may be present in the reconstructed data, and the presence of such artefacts can degrade XCT image quality and affect quantitative analysis. If the product of the X-ray spectrum and the quantum detection efficiency (QDE) of the detector are known, alongside the material of the scanned object, then beam hardening artefacts can be corrected algorithmically.
View Article and Find Full Text PDFX-ray computed tomography (CT) is a radiographic scanning technique for visualising cross-sectional images of an object non-destructively. From these cross-sectional images it is possible to evaluate internal dimensional features of a workpiece which may otherwise be inaccessible to tactile and optical instruments. Beam hardening is a physical process that degrades the quality of CT images and has previously been suggested to influence dimensional measurements.
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