A Novel Method of Correcting the Sinogram Data for Positrion Emission Tomography

Author

Chen, Yang ; Feng, Qianjin ; Chen, Wufan ; Zhan, Jie ; Shi, Pengcheng

Author_Institution

Southern Med. Univ., Guangzhou

fYear

2007

fDate

23-27 May 2007

Firstpage

1375

Lastpage

1378

Abstract

In the problems of statistical reconstruction of PET images, Bayesian reconstruction, or maximum a posteriori (MAP) method, has proved its superiority over others among all the regularization methods. To further improve the reconstruction, this paper presents a novel statistical image reconstruction method based on coupled feedback (CF) iterative model for positron emission tompgraphy (PET). This CF iterative algorithm updates the noisy emission sinogram (the measurements of the detectors) using the latest reconstructed image. The experiments and the performance analysis confirm the virtue of the new method.

Keywords

image reconstruction; iterative methods; medical image processing; positron emission tomography; statistical analysis; Bayesian reconstruction; PET images; coupled feedback iterative model; maximum a posteriori method; positron emission tomography; sinogram data; statistical image reconstruction method; statistical reconstruction; Bayesian methods; Biomedical engineering; Biomedical imaging; Feedback; Image reconstruction; Iterative algorithms; Iterative methods; Maximum likelihood detection; Maximum likelihood estimation; Positron emission tomography;

fLanguage

English

Publisher

ieee

Conference_Titel

Complex Medical Engineering, 2007. CME 2007. IEEE/ICME International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-1077-4

Electronic_ISBN

978-1-4244-1078-1

Type

conf

DOI

10.1109/ICCME.2007.4381969

Filename

4381969