Nonlinear backprojection for tomographic reconstruction

Author

Andía, Blanca I. ; Sauer, Ken D. ; Bouman, Charles A.

Author_Institution

Dept. of Electr. Eng., Notre Dame Univ., IN, USA

Volume

49

Issue

1

fYear

2002

fDate

2/1/2002 12:00:00 AM

Firstpage

61

Lastpage

68

Abstract

This paper focuses on a tomographic image reconstruction method, which will be referred to as nonlinear backprojection (NBP). Rather than explicitly statistically modeling the forward process and the unknown image, we train an optimal NBP operator that can be implemented noniteratively. Under appropriate assumptions, the method forms its estimate by applying nonlinear filters to sinogram data, followed by conventional backprojection. The nonlinear filters are designed through off-line training. NBP shows promising results relative to both filtered backprojection and maximum a posteriori probability Bayesian methods

Keywords

computerised tomography; image reconstruction; nonlinear filters; filtered backprojection; maximum a posteriori probability Bayesian methods; nonlinear backprojection; nonlinear filters; sinogram; tomographic image reconstruction; Bayesian methods; Cost function; Filtering; Image reconstruction; Maximum likelihood estimation; Nonlinear filters; Probability; Signal to noise ratio; Statistical analysis; Tomography;

fLanguage

English

Journal_Title

Nuclear Science, IEEE Transactions on

Publisher

ieee

ISSN

0018-9499

Type

jour

DOI

10.1109/TNS.2002.998682

Filename

998682