Emission Image Reconstruction Based on Incremental Optimization Transfer Algorithm

Author

Yan, Jianhua ; Yu, Jun

Author_Institution

Huazhong Univ. of Sci. & Technol., Wuhan

Volume

2

fYear

2006

fDate

20-24 June 2006

Firstpage

266

Lastpage

269

Abstract

We introduce the incremental optimization transfer framework to estimate emission means in positron emission tomography. The proposed algorithms accelerate convergence speeds and ensure global convergence (to a stationary point) under mild regularity conditions without inconvenient relaxation parameters. In experiments using synthetic data and real phantom data, it was found that, for a fixed level of background noise, the proposed could provide high quality reconstructed images

Keywords

gradient methods; image reconstruction; image resolution; medical image processing; optimisation; positron emission tomography; image quality; incremental optimization transfer algorithm; positron emission estimation; positron emission image reconstruction; positron emission tomography; Acceleration; Distributed computing; Electrical capacitance tomography; Image converters; Image reconstruction; Imaging phantoms; Iterative algorithms; Maximum likelihood estimation; Optical computing; Positron emission tomography;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on

Conference_Location

Hanzhou, Zhejiang

Print_ISBN

0-7695-2581-4

Type

conf

DOI

10.1109/IMSCCS.2006.221

Filename

4673713