On the Convergence of Generalized Simultaneous Iterative Reconstruction Algorithms

Author

Wang, Jiong ; Zheng, Yibin

Author_Institution

Dept. of Electr. & Comput. Eng, Virginia Univ., Charlottesville, VA

Volume

16

Issue

1

fYear

2007

Firstpage

1

Lastpage

6

Abstract

In this paper, we generalize the widely used simultaneous block iterative reconstruction algorithm and show that it converges, at a linear rate, to a weighted least-squares and weighted minimum-norm reconstruction. Our theoretical result provides a much simpler proof of the convergence properties obtained by Jiang and Wang and covers a much more general class of algorithms. The frequency domain iterative reconstruction algorithm is then introduced as a special application of our theory

Keywords

image reconstruction; iterative methods; least squares approximations; medical image processing; biomedical imaging; convergence properties; frequency domain iterative algorithm; iterative reconstruction algorithms; weighted least-squares; weighted minimum-norm reconstruction; Computed tomography; Convergence; Frequency domain analysis; Image reconstruction; Iterative algorithms; Iterative methods; Partitioning algorithms; Reconstruction algorithms; Size measurement; Subspace constraints; Biomedical imaging; image reconstruction; iterative methods; signal reconstruction; tomography; Algorithms; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Reproducibility of Results; Sensitivity and Specificity;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2006.887725

Filename

4032830