Enhancement of patient-motion-disturbed (dental) Cone Beam Computed Tomography (CBCT) data.

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CBCT-data are reconstructed from two-dimensional (2D) radiographs that are acquired over several seconds and a circular trajectory of x-ray source and detector around the patients' head. During the several seconds patients often move, which in the regular three-dimensional (3D) reconstruction is not taken care of. In dental applications, motion of the mandible relative to the skull may introduced additional challenges. Patient motion causes motion blur and artifacts in the 3D-data. Our project aims at developing an iterative algorithm basing on the 2D projection images capable to correct for such motion. The algorithm also has to deal with the local tomography problem, which is very relevant to small-volume dental CBCTs. In addition, it shall be capable to handle motion of the two components skull and mandible relative to one another.