Reduction of beam hardening artifacts on real C-arm CT data using polychromatic statistical image reconstruction.

This work aims at the compensation of beam hardening artifacts by the means of an extended three-dimensional polychromatic statistical reconstruction to be applied for flat panel cone-beam CT. We implemented this reconstruction technique as being introduced by Elbakri et al. (2002) [1] for a multi-GPU system, assuming the underlying object consists of several well-defined materials. Furthermore, we assume one voxel can only contain an overlap of at most two materials, depending on its density value. Given the X-ray spectrum, the procedure enables to reconstruct the energy-dependent attenuation values of the volume. We evaluated the method by using flat-panel cone-beam CT measurements of structures containing small metal objects and clinical head scan data. In comparison with the water-corrected filtered backprojection, as well as a maximum likelihood reconstruction with a consistency-based beam hardening correction, our method features clearly reduced beam hardening artifacts and a more accurate shape of metal objects. Our multi-GPU implementation of the polychromatic reconstruction, which does not require any image pre-segmentation, clearly outperforms the standard reconstructions of objects, with respect to beam hardening even in the presence of metal objects inside the volume. However, remaining artifacts, caused mainly by the limited dynamic range of the detector, may have to be addressed in future work.

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Copyright © 2019. Published by Elsevier GmbH.