Image Reconstruction Using an Improved MAP-EM Method in X-ray CT

Author

Dong, Baoyu

Author_Institution

Sch. of Electr. & Inf. Eng., Dalian Jiaotong Univ., Dalian, China

Volume

1

fYear

2009

fDate

11-12 April 2009

Firstpage

483

Lastpage

486

Abstract

An improved MAP-EM algorithm is proposed for Bayesian reconstruction in X-ray CT based upon Markov random field priors and the Poisson data model. The improved algorithm can yield better reconstruction than MAP-EM algorithm, and its convergence is faster. The improved method is verified by applications to computer simulation data and real X-ray CT data from two aluminous tubes scans. Experiments results show this method is effective. Reconstructed slice images of the improved algorithm are accurate and clear.

Keywords

Markov processes; Poisson distribution; X-ray microscopy; belief networks; computerised tomography; expectation-maximisation algorithm; image reconstruction; medical image processing; random processes; Bayesian method; Markov random field; Poisson distribution; X-ray CT; aluminous tube scan; computer simulation data; computerised tomography; image reconstruction; improved MAP-EM method; maximum a posteriori expectation maximisation algorithm; Bayesian methods; Biomedical imaging; Computed tomography; Computer simulation; Detectors; Geometry; Image reconstruction; Maximum likelihood estimation; Random variables; X-ray imaging; Bayesian theorem; Image reconstruction; MAP-EM; X-ray CT;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on

Conference_Location

Zhangjiajie, Hunan

Print_ISBN

978-0-7695-3583-8

Type

conf

DOI

10.1109/ICMTMA.2009.102

Filename

5203016