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OEM X-ray Components



CT Reconstruction

Special reconstruction methods for an extended CT application range

The CERA-SRM add-on module extends the supported CT application range with half-beam reconstruction, grid tomography, and quantitative region-of-interest tomography.

Half-beam reconstruction for nearly double field-of-view in one 360° scan
The flexible half-beam reconstruction algorithm in CERA supports scan setups with shifted detector or with shifted rotation axis. The algorithm also considers known offsets from the ideal system geometry like a tilted detector or a tumbling of the rotation axis. Thus, an excellent image quality is even possible in case of non-ideal scan trajectories.
The key advantages are

  • Up to 1.8² times larger scan volume in a single 360° scan
  • Half-beam scan setups with shifted detector, shifted rotation axis, or a combination of both
Shifted detector half-beam CT
Shifted detector half-beam CT


Multiple extension of the field-of-view using grid tomography
The grid tomography or extended field-of-view reconstruction allows increasing the measurement volume diameter by systematic combination of multiple circular scans at horizontally shifted detector positions. Thus, even large objects which exceed the field-of-view diameter multiple times can be scanned with an appropriate CT system.
Our precise implementation helps to avoid image artifacts, which typically occur with simple projection stitching. Moreover, the algorithm even supports non-ideal detector shifts, if the source positions match.

Quantitative region-of-interest CT – systematic combination of overview and ROI scans
Quantitative region-of-interest CT – systematic combination of overview and ROI scans

Quantitative region-of-interest tomography
Pure truncation correction for region-of-interest (ROI) reconstruction helps to mitigate image artifacts. However, the unknown beam absorption of object parts outside of the ROI necessarily degrades image quality.
The ROI reconstruction algorithm in CERA-SRM supports to achieve quantitative CT values by intelligently combining the ROI scan with an overview scan of the whole sample. Thus, image artifacts of conventional ROI methods, which merely use truncation correction, are avoided

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