A new novel PET/CT reconstruction algorithm by using prior image model with simulated annealing process

Author

See, Eric S K

Author_Institution

Dept. of ICT, Hong Kong Inst. of Vocational Educ., China

fYear

2005

fDate

13-16 Dec. 2005

Firstpage

661

Lastpage

664

Abstract

This paper shows how to combine the prior anatomical information with projected data in the PET image reconstruction. The new proposed algorithm uses powerful penalized-likelihood regularization method with the prior image model and simulated annealing process to suppress the Poisson noise in data. From the simulation, the new algorithm demonstrates significant improvement in the quality of reconstructed images as compared with the images obtained from EM-ML and minimum cross-entropy algorithms.

Keywords

expectation-maximisation algorithm; image denoising; image reconstruction; positron emission tomography; simulated annealing; PET image reconstruction; Poisson noise suppression; expectation maximization; maximum likelihood estimation; penalized-likelihood regularization method; positron emission tomography; prior anatomical information; prior image model; simulated annealing process; Computed tomography; Image reconstruction; Image resolution; Iterative algorithms; Maximum likelihood detection; Maximum likelihood estimation; Positron emission tomography; Reconstruction algorithms; Simulated annealing; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Signal Processing and Communication Systems, 2005. ISPACS 2005. Proceedings of 2005 International Symposium on

Print_ISBN

0-7803-9266-3

Type

conf

DOI

10.1109/ISPACS.2005.1595496

Filename

1595496