Recursive least squares image reconstruction

Author

Zheng, Yibin

Author_Institution

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

Volume

2

fYear

2001

fDate

4-7 Nov. 2001

Firstpage

1702

Abstract

A recursive least squares algorithm is formulated in the context of image reconstruction, using computed tomography (CT) as an example. Compared to traditional algebraic reconstruction techniques (ART), the new algorithm converges in as little as one iteration and has the ability to incorporate a priori information such as image smoothness. Several approximations of the algorithm are proposed and it is demonstrated that they can be implemented for practical image reconstruction problems and obtain very good results.

Keywords

computerised tomography; convergence of numerical methods; image reconstruction; iterative methods; least squares approximations; medical image processing; recursive estimation; CT imaging; a priori information; computed tomography; convergence; image reconstruction; image smoothness; iteration; recursive least squares algorithm; Acoustic measurements; Computed tomography; Equations; Extraterrestrial measurements; Fourier transforms; Image reconstruction; Least squares methods; Magnetic field measurement; Magnetic resonance imaging; Subspace constraints;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 2001. Conference Record of the Thirty-Fifth Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-7803-7147-X

Type

conf

DOI

10.1109/ACSSC.2001.987775

Filename

987775