Noise and resolution of Bayesian reconstruction for multiple image configurations

Author

Chinn, Garry ; Huang, Sung-Cheng

Author_Institution

Div. of Nucl. Med. & Biophys., Univ. of California Los Angeles Sch. of Med., Los Angeles, CA, USA

Volume

40

Issue

6

fYear

1993

fDate

12/1/1993 12:00:00 AM

Firstpage

2059

Lastpage

2063

Abstract

Images reconstructed by Bayesian and maximum-likelihood (ML) using a Gibbs prior with prior β were compared with images produced by filtered backprojection (FBP) from sinogram data simulated with different counts and image configurations. Bayesian images were generated by the OSL algorithm accelerated by an overrelaxation parameter. For relatively low β, Bayesian images can yield an overall improvement to the images compared to ML reconstruction. However, for larger β, Bayesian images degrade from the standpoint of noise and quantitation. Compared to FBP, the ML images were superior in a mean-square error sense in regions of low activity level and for small structures. At a comparable noise level to FBP, Bayesian reconstruction can be used to effectively recover higher resolution images. The overall performance is dependent on the image structure and the weight of the Bayesian prior

Keywords

Bayes methods; computerised tomography; image reconstruction; medical image processing; radioisotope scanning and imaging; Bayesian images; Bayesian reconstruction; Gibbs prior; filtered backprojection; image structure; mean-square error; multiple image configurations; overrelaxation parameter; sinogram data; Acceleration; Attenuation; Bayesian methods; Degradation; Detectors; Image generation; Image reconstruction; Image resolution; Noise level; Tomography;

fLanguage

English

Journal_Title

Nuclear Science, IEEE Transactions on

Publisher

ieee

ISSN

0018-9499

Type

jour

DOI

10.1109/23.273561

Filename

273561