Application of Raw Data Consistency Conditions in Cone-Beam CT X-ray Computed Tomography scanning is a standard
procedure in medical imaging.
Though the fundamentals of reconstructing the density of
an object from lower dimensional projection images is
well understood,
real systems have to deal with additional sources of
corruption.
These can either be of geometric nature, from imperfect
calibration or patient movement or physical effects like
beam hardening and scatter.
Many methods have been proposed to correct for these
problems. Most of them rely on prior knowledge or
additional equipment.
However the inconsistency introduced by those corruptions
can be quantified using redundancies in CT raw data.
By numerically minimizing this inconsistency using
appropriate compensation models, artifact reduction can
be achieved without using prior knowledge or external
equipment.
The goal of this project is to develop novel artifact
compensation algorithms for cone-beam CT, based on raw-
data consistency conditions and to extend and improve
existing
compensation algorithms for calibration and motion
compensation. A particular sub-goal for extension is, to
extend the applicability of consistency-condition-based
algorithms to trajectories
required for theoretically exact reconstruction, like
helix or circle-line trajectories. | Project manager: Prof. Dr.-Ing. habil. Andreas Maier, Dr.-Ing. Frank Dennerlein, Dr. rer. biol. hum. Nicole Maaß
Project participants: Tobias Würfl, M. Sc.
Keywords: Computed Tomography, 3D-reconstruction, Consistency Conditions
Duration: 1.5.2016 - 30.4.2019
Sponsored by: Siemens AG, Healthcare Sector, Erlangen
Contact: Würfl, Tobias Phone +49 9131 85 27799, Fax +49 9131 85 27270, E-Mail: tobias.wuerfl@fau.de
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