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Proceedings Paper

Kinetic parameter reconstruction for motion compensation in transmission tomography
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Paper Abstract

Model based iterative reconstruction (MBIR) algorithms have recently been applied to computed tomography and demonstrated superior image quality. This algorithmic framework also provides us the flexibility to incorporate more sophisticated models of the data acquisition process. In this paper, we present the kinetic parameter iterative reconstruction (KPIR) algorithm which estimates voxel values as a function of time in the MBIR framework. We introduce a parametric kinetic model for each voxel, and estimate the kinetic parameters directly from the data. Results on phantom study and clinical data show that the proposed method can significantly reduce motion artifacts in the reconstruction.

Paper Details

Date Published: 8 February 2011
PDF: 7 pages
Proc. SPIE 7873, Computational Imaging IX, 78730T (8 February 2011); doi: 10.1117/12.887843
Show Author Affiliations
Zhou Yu, GE Healthcare Technologies (United States)
Jean-Baptiste Thibault, GE Healthcare Technologies (United States)
Jiao Wang, Univ. of Notre Dame (United States)
Charles A. Bouman, Purdue Univ. (United States)
Ken D. Sauer, Univ. of Notre Dame (United States)


Published in SPIE Proceedings Vol. 7873:
Computational Imaging IX
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)

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