Model-based image reconstruction for dual-energy X-ray CT with fast KVP switching

Authors:
Wonseok Huh;Jeffrey A. Fessler
Affiliations:
Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, MI;Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, MI
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

The most recent generation of X-ray CT systems can collect dual energy (DE) sinograms by rapidly switching the X-ray tube voltage between two levels for alternate projection views. This reduces motion artifacts in DE imaging, but yields sinograms that may be angularly under-sampled. This paper describes an iterative algorithm for statistical image reconstruction of material component images (e.g., soft tissue and bone) directly from such under-sampled DE data, without resorting to the interpolation operations required by conventional DE reconstruction methods.