Segmentation-free statistical image reconstruction for polyenergetic X-ray computed tomography

Author

Elbakri, Idris A. ; Fessler, Jefrey A.

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA

fYear

2002

fDate

2002

Firstpage

828

Lastpage

831

Abstract

This paper describes a statistical iterative reconstruction method for X-ray CT based on a physical model that accounts for the polyenergetic X-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. The algorithm accommodates mixtures of tissues with known mass attenuation coefficients but unknown densities. We formulate a penalized-likelihood approach for this polyenergetic model based on Poisson statistics.

Keywords

X-ray absorption; computerised tomography; image reconstruction; iterative methods; medical image processing; statistics; Poisson statistics; X-ray CT; energy-dependent attenuation; known mass attenuation coefficients; measurement nonlinearities; medical diagnostic imaging; physical model; polyenergetic model; statistical iterative reconstruction method; tissue mixtures; unknown densities; Attenuation measurement; Computed tomography; Energy measurement; Image reconstruction; Image segmentation; Iterative algorithms; Iterative methods; Reconstruction algorithms; Statistics; X-ray imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging, 2002. Proceedings. 2002 IEEE International Symposium on

Print_ISBN

0-7803-7584-X

Type

conf

DOI

10.1109/ISBI.2002.1029387

Filename

1029387