Statistical reconstruction for quantitative CT applications

Author

Elbakri, Idris A. ; Zhang, Yingying ; Chen, Laigao ; Clinthorne, Neal H. ; Fessler, Jeffrey A.

Author_Institution

Fischer Imaging, Denver, CO, USA

Volume

4

fYear

2003

fDate

19-25 Oct. 2003

Firstpage

2978

Abstract

This paper summarizes considerations in developing statistical reconstruction algorithms for polyenergetic X-ray CT. The algorithms are based on Poisson statistics and polyenergetic X-ray attenuation physics and object models. In single-kVp scans, object models enable estimates of the contributions of bone and soft tissue at every pixel, based on prior assumptions about the tissue properties. In dual-kVp scans, one can estimate water and bone images independently. Preliminary results with fan-beam data from two cone beam systems show better accuracy for iterative methods over FBP.

Keywords

bone; computerised tomography; image reconstruction; iterative methods; maximum likelihood estimation; medical image processing; statistical analysis; Poisson statistics; X-ray computed tomography; bone images; cone beam systems; dual-energy imaging; dual-kVp scans; fan-beam data; iterative methods; maximum a posteriori estimation; object models; penalized-likelihood image reconstruction; polyenergetic X-ray CT; polyenergetic X-ray attenuation physics; quantitative CT applications; single-kVp scans; soft tissue; statistical reconstruction algorithms; tissue properties; water images; Attenuation; Biological tissues; Bones; Computed tomography; Image reconstruction; Iterative methods; Physics; Reconstruction algorithms; Statistics; X-ray imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

Nuclear Science Symposium Conference Record, 2003 IEEE

ISSN

1082-3654

Print_ISBN

0-7803-8257-9

Type

conf

DOI

10.1109/NSSMIC.2003.1352510

Filename

1352510