Investigation of the linearized spectral contribution in the simultaneous estimation of spectra and basis images in multispectral CT reconstruction

Buxin Chen; Zheng Zhang; Dan Xia; Emil Y. Sidky; Xiaochuan Pan

doi:10.1117/12.2581693

15 February 2021 Investigation of the linearized spectral contribution in the simultaneous estimation of spectra and basis images in multispectral CT reconstruction

Buxin Chen, Zheng Zhang, Dan Xia, Emil Y. Sidky, Xiaochuan Pan

Author Affiliations +

Proceedings Volume 11595, Medical Imaging 2021: Physics of Medical Imaging; 115951F (2021) https://doi.org/10.1117/12.2581693
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

Simultaneous estimation of spectra and basis images in multispectral CT reconstruction employs a data model with unknown spectra. One approach is based on the linearization of the data model, which leads to two linear terms, with regards to the basis image and to the spectrum. The latter one, i.e., the linearized matrix of spectral contribution, is new, to the best of our knowledge, and warrants investigations. In this work, we have characterized the conditioning of the linearized matrix of spectral contribution using singular value decomposition (SVD). We have also proposed a SVD-based preconditioner for the matrix and incorporated it in a constrained optimization problem for recovering the spectrum. The results have showed improved conditioning of the matrix and accurate recovery of the spectrum by use of the SVD-based preconditioner.

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Buxin Chen, Zheng Zhang, Dan Xia, Emil Y. Sidky, and Xiaochuan Pan "Investigation of the linearized spectral contribution in the simultaneous estimation of spectra and basis images in multispectral CT reconstruction", Proc. SPIE 11595, Medical Imaging 2021: Physics of Medical Imaging, 115951F (15 February 2021); https://doi.org/10.1117/12.2581693

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