Background Matters: A Correction Scheme for Dynamic Iterative CBCT with Limited Grid Size

Oliver Taubmann, Gunter Lauritsch , Gregor Krings, Andreas Maier


Published in:Fully3D 2017 Proceedings


Dynamic cone-beam computed tomography (CBCT) imaging of the thorax, i. e. time-resolved reconstruction w. r. t. cardiac or respiratory motion, requires sophisticated algorithms, many of which are iterative and computationally expensive in terms of both runtime and memory. For the latter, hardware constraints pose a considerable challenge insofar as the volume grid cannot be chosen arbitrarily large. On the other hand, choosing a small grid may lead to severe artifacts if the object exceeds the size of the reconstruction domain. Additionally, lateral truncation of the projection data is commonly encountered as, e. g., flat panel detectors employed in interventional C-arm devices are not large enough to simultaneously image the entire width of the thorax in most patients. In iterative reconstruction, mild data truncation artifacts can also be alleviated by reconstructing on a sufficiently large grid. We present a simple model to incorporate information from outside the target grid in dynamic reconstruction. Its main component is the reconstruction of a static background image used to precompute an additive data correction term, which can be used in combination with any dynamic iterative reconstruction method. The effectiveness of our approach is demonstrated in a numerical phantom and clinical patient data.
Oliver Taubmann
Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg
Gunter Lauritsch
Siemens Healthcare GmbH
Gregor Krings
University Medical Center Utrecht
Andreas Maier
Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg
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