Implementation and Evaluation of Two Helical CT Reconstruction Algorithms in CIVA
Résumé
The large majority of industrial CT systems reconstruct the 3D volume by using an acquisition on a circular trajectory.
However, when inspecting long objects which are highly anisotropic, this scanning geometry creates severe artifacts in the
reconstruction. For this reason, the use of an advanced CT scanning method like helical data acquisition is an ecient way to
address this aspect known as the long-object problem. Recently, several analytically exact and quasi-exact inversion formulas for
helical cone-beam reconstruction have been proposed. Among them, we identified two algorithms of interest for our case. These
algorithms are exact and of filtered back-projection structure. In this work we implemented the filtered-backprojection (FBP) and
backprojection-filtration (BPF) algorithms of Zou and Pan (2004). For performance evaluation, we present a numerical comparison
of the two selected algorithms with the helical FDK algorithm using both complete (noiseless and noisy) and truncated data
generated by CIVA (the simulation platform for non-destructive testing techniques developed at CEA).