Comparison of algebraic and analytical approaches to the formulation of the statistical model-based reconstruction problem for X-ray computed tomography.
The main aim of this paper is to investigate properties of our originally formulated statistical model-based iterative approach applied to the image reconstruction from projections problem which are related to its conditioning, and, in this manner, to prove a superiority of this approach over ones recently used by other authors. The reconstruction algorithm based on this conception uses a maximum likelihood estimation with an objective adjusted to the probability distribution of measured signals obtained from an X-ray computed tomography system with parallel beam geometry. The analysis and experimental results presented here show that our analytical approach outperforms the referential algebraic methodology which is explored widely in the literature and exploited in various commercial implementations.
Institute of Computational Intelligence, Czestochowa University of Technology, Armii Krajowej 36, 42-200 Czestochowa, Poland. Electronic address: robert.cierniak@iisi.pcz.pl.
Robert
R
Cierniak
Institute of Computational Intelligence, Czestochowa University of Technology, Armii Krajowej 36, 42-200 Czestochowa, Poland.
Anna
A
Lorent
D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016013:Likelihood Functions; D015233:Models, Statistical; D014057:Tomography, X-Ray Computed / Q000379:methods*
Image reconstruction from projections; Statistical reconstruction algorithm; X-ray computed tomography