Relations between system matrices and the complete data space in MLEM using the Kullback-Leibler distance

Author

Huh, Sam S. ; Clinthorne, Neal H. ; Haefner, A. ; Chivers, D. ; Mihailescu, Lucian ; Vetter, K.

Author_Institution

Appl. Nucl. Phys. Program, Lawrence Berkeley Nat. Lab., Berkeley, CA, USA

fYear

2013

fDate

Oct. 27 2013-Nov. 2 2013

Firstpage

1

Lastpage

6

Abstract

We present a quantitative method for relating system matrices to the complete-data space in maximum likelihood expectation maximization (MLEM) using the Kullback-Leibler distance. We show that a more accurate system matrix has a smaller Kullback-Leibler (KL) distance. System matrices of a coded aperture imaging system were used for comparison. The calculation of the KL distance is based on the Monte Carlo integral. We note that system matrices for the KL distance evaluation should be generated by underlying physics processes.

Keywords

Monte Carlo methods; image reconstruction; matrix algebra; maximum likelihood estimation; Kullback-Leibler distance; Monte Carlo integral; coded aperture imaging system; complete-data space; image reconstruction; maximum likelihood expectation maximization; system matrices; Apertures; Attenuation; Detectors; Imaging; Monte Carlo methods; Position measurement; Ray tracing;

fLanguage

English

Publisher

ieee

Conference_Titel

Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2013 IEEE

Conference_Location

Seoul

Print_ISBN

978-1-4799-0533-1

Type

conf

DOI

10.1109/NSSMIC.2013.6829795

Filename

6829795