Title :
Image Reconstruction Using an Improved MAP-EM Method in X-ray CT
Author_Institution :
Sch. of Electr. & Inf. Eng., Dalian Jiaotong Univ., Dalian, China
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;
Conference_Titel :
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-0-7695-3583-8
DOI :
10.1109/ICMTMA.2009.102
