A primal dual proximal point method of Chambolle-Pock algorithm for total variation image reconstruction

Author

Yuchao Tang ; Yong Cai ; Xiang Wang ; Jigen Peng

Author_Institution

Dept. of Math., Nanchang Univ., Nanchang, China

fYear

2013

fDate

19-20 Oct. 2013

Firstpage

6

Lastpage

10

Abstract

Total variation (TV) minimization problems are widely used for solving incomplete data problems in computed tomography (CT) image reconstruction. The present paper investigates a primal dual proximal point method of Chambolle-Pock algorithm to solve the CT image reconstruction problem which consisting the sum of l₂ data fidelity term and TV regularization term. We tested these methods on computer simulated data, and they exhibited good performance when used to few-view and limited-angle CT image reconstruction.

Keywords

computerised tomography; image reconstruction; medical image processing; minimisation; Chambolle-Pock algorithm; computed tomography; few-view CT image reconstruction; l₂ data fidelity term; limited-angle CT image reconstruction; primal dual proximal point method; total variation image reconstruction; total variation minimization problems; total variation regularization term; Computed tomography; Convergence; Data models; Image reconstruction; Noise; Optimization; TV;

fLanguage

English

Publisher

ieee

Conference_Titel

Medical Imaging Physics and Engineering (ICMIPE), 2013 IEEE International Conference on

Conference_Location

Shenyang

Print_ISBN

978-1-4799-6305-8

Type

conf

DOI

10.1109/ICMIPE.2013.6864492

Filename

6864492