Adapted acquisition trajectory and iterative reconstruction for few-views CT inspection
Résumé
One of the major stakes of industrial Computed Tomography (CT) is the reduction of acquisition time in order to allow its use
directly in production lines. With the introduction of robotic systems, which are capable of taking each piece from the production
conveyor and to manipulate them inside an X-ray beam or to directly move the X-ray equipment around the object, new
opportunities arise. Especially, the inspection trajectory is no more limited to one acquisition plane and when combined with an
adequate algorithm, a satisfactory CT reconstruction can be obtained from few X-ray projections.
Such 3D trajectory makes the classical analytic reconstruction algorithms inappropriate and requires the use of 3D iterative
reconstruction algorithms. In this work, we focus on two iterative algorithms, the well-known Simultaneous Algebraic
Reconstruction Technique (SART) and the Discrete Algebraic Reconstruction Technique (DART), which integrates prior
knowledge on the object, to perform 3D reconstructions from a limited data set. The performances of both algorithms on complex
trajectories are evaluated in simulation environment using the CIVA software from CEA List and real acquisitions on non
standard trajectories are performed with the robotic platform and reconstruction results with SART and DART algorithms are
presented and compared.
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