Abstract:
Systems and methods for non-destructive testing by computed tomography are provided. The system can include a stationary radiation source, a stage, and a plurality of stationary radiation detectors. The source can be configured to emit, from a focal point, a beam of penetrating radiation having a three-dimensional geometry and to direct the beam in a path incident upon a target. The stationary radiation source can be positioned with respect to the plurality of stationary radiation detectors and the stage such that, a first plurality of beam segment paths is defined between the focal point and respective sensing faces of the plurality of radiation detectors and at least one second beam segment path is defined between the focal point and a predetermined gap.
Abstract:
A method for detecting geometrical imaging properties of a flat panel detector (12) in an X-ray testing system comprises the steps of: disposing a calibrating body (13) between an X-ray beam source (11) and the flat panel detector (12), the calibrating body (13) comprising at least one discrete geometrical object (30); recording at least one X-ray image of the calibrating body (13) with the flat panel detector (12), with at least one discrete geometrical figure (32) being generated in the X-ray image by imaging the at least one discrete geometrical object (30) of the calibrating body (13); and determining the positionally dependent distortion error of the flat panel detector (12) from the at least one X-ray image based on at least one feature of the at least one discrete geometrical figure (32). All features of the at least one discrete geometrical figure (32) used for determining the positionally dependent distortion error are independent from the dimensions of the calibrating body (13).
Abstract:
A computed tomography method for determining a volumetric representation of a sample (13) comprises an initial reconstruction step (22) for reconstructing initial volume data (23) of the sample (13) from x-ray projections (21) of the sample (13) taken by an x-ray system (10), a step (24) of determining a part of the reconstructed initial sample volume to be updated, and an iterative update process (32) for generating, using an iterative reconstruction method, updated volume data (23) only for the part of the volume data (23) determined to be updated. The method comprises, in said step (24) of determining the part of the sample volume to be updated, individually evaluating for every single voxel in said volume data (23), based on available quality information for the reconstructed volume data (23), whether or not this voxel fulfils a predetermined condition indicating that an update is required for this voxel, and, in said iterative update process (32), generating said updated volume data (23) only for those voxels for which it has been determined that an update is required.
Abstract:
Scatter correction for tomography: for each position, two images are aquired, a first image without and a second image with a scatter reducing aperture plate (50). A scatter image is calculated by subtracting the second image from the first image. The apertures (48) in the scatter reducing plate (50) are arranged hexagonally in order to optimise the packaging density of the apertures.
Abstract:
A computed tomography method for determining a volumetric representation of a sample (13), comprising a first reconstruction (22a) for reconstructing first reconstructed volume data (23a) of the sample (13) from first x-ray projection data (21a) of the sample (13) taken by an x-ray system (10), a second reconstruction (22b) for reconstructing second reconstructed volume data (23b) of the sample (13) from second x- ray projection data (21b) of the sample (13) taken by an x-ray system (10), characterized by calculating first individual confidence measures (28a) for single voxels of said first reconstructed volume data (23a), calculating second individual confidence measures (28b) for single voxels of said second reconstructed volume data (23b), and calculating, in a subsequent step (35), at least one resulting set of individual values (36, 37, 38) for each voxel based on said first individual confidence measures (28a) and said second individual confidence measures (28b).