TY - GEN

T1 - Spectral response compensation for photon-counting clinical x-ray CT using sinogram restoration

AU - Srivastava, Somesh

AU - Cammin, Jochen

AU - Fung, George S.K.

AU - Tsui, Benjamin M.W.

AU - Taguchi, Katsuyuki

PY - 2012

Y1 - 2012

N2 - The x-ray spectrum recorded by a photon-counting x-ray detector (PCXD) is distorted due to the following physical effects which are independent of the count rate: finite energy-resolution, Compton scattering, charge-sharing, and Kescape. If left uncompensated, the spectral response (SR) of a PCXD due to the above effects will result in image artifacts and inaccurate material decomposition. We propose a new SR compensation (SRC) algorithm using the sinogram restoration approach. The two main contributions of our proposed algorithm are: (1) our algorithm uses an efficient conjugate gradient method in which the first and second derivatives of the cost functions are directly calculated analytically, whereas a slower optimization method that requires numerous function evaluations was used in other work; (2) our algorithm guarantees convergence by combining the non-linear conjugate gradient method with line searches that satisfy Wolfe conditions, whereas the algorithm in other work is not backed by theorems from optimization theory to guarantee convergence. In this study, we validate the performance of the proposed algorithm using computer simulations. The bias was reduced to zero from 11%, and image artifacts were removed from the reconstructed images. Quantitative K-edge imaging in possible only when SR compensation is done.

AB - The x-ray spectrum recorded by a photon-counting x-ray detector (PCXD) is distorted due to the following physical effects which are independent of the count rate: finite energy-resolution, Compton scattering, charge-sharing, and Kescape. If left uncompensated, the spectral response (SR) of a PCXD due to the above effects will result in image artifacts and inaccurate material decomposition. We propose a new SR compensation (SRC) algorithm using the sinogram restoration approach. The two main contributions of our proposed algorithm are: (1) our algorithm uses an efficient conjugate gradient method in which the first and second derivatives of the cost functions are directly calculated analytically, whereas a slower optimization method that requires numerous function evaluations was used in other work; (2) our algorithm guarantees convergence by combining the non-linear conjugate gradient method with line searches that satisfy Wolfe conditions, whereas the algorithm in other work is not backed by theorems from optimization theory to guarantee convergence. In this study, we validate the performance of the proposed algorithm using computer simulations. The bias was reduced to zero from 11%, and image artifacts were removed from the reconstructed images. Quantitative K-edge imaging in possible only when SR compensation is done.

KW - Photon-counting detectors

KW - clinical x-ray CT

KW - conjugate gradient

KW - convergent algorithms

KW - image reconstruction

KW - maximum likelihood estimation

KW - optimization methods

KW - sinogram restoration

UR - http://www.scopus.com/inward/record.url?scp=84860356080&partnerID=8YFLogxK

U2 - 10.1117/12.911394

DO - 10.1117/12.911394

M3 - Conference contribution

AN - SCOPUS:84860356080

SN - 9780819489623

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2012

T2 - Medical Imaging 2012: Physics of Medical Imaging

Y2 - 5 February 2012 through 8 February 2012

ER -