Regularized emission image reconstruction using imperfect side information

Author

Fessler, Jeffrey A. ; Clinthorne, Neal H. ; Rogers, W. Leslie

Author_Institution

Div. of Nucl. Med., Michigan Univ., Ann Arbor, MI, USA

Volume

39

Issue

5

fYear

1992

fDate

10/1/1992 12:00:00 AM

Firstpage

1464

Lastpage

1471

Abstract

A spatially variant penalized-likelihood method for tomographic image reconstruction based on a weighted Gibbs penalty was investigated. The penalty weights are determined from structural side information, such as the locations of anatomical boundaries in high-resolution magnetic resonance images. Such side information will be imperfect in practice, and a simple simulation demonstrated the importance of accounting for the errors in boundary locations. Methods are discussed for prescribing the penalty weights when the side information is noisy. Simulation results suggest that even imperfect side information is useful for guiding spatially variant regularization

Keywords

biomedical NMR; computerised tomography; image reconstruction; medical image processing; radioisotope scanning and imaging; anatomical boundaries; high-resolution magnetic resonance images; imperfect side information; medical diagnostic imaging; regularized emission image reconstruction; spatially variant penalized-likelihood method; structural side information; tomographic image reconstruction; weighted Gibbs penalty; Biomedical imaging; Gaussian noise; Image reconstruction; Iterative methods; Magnetic noise; Magnetic resonance; Maximum likelihood estimation; Nuclear medicine; Reconstruction algorithms; Tomography;

fLanguage

English

Journal_Title

Nuclear Science, IEEE Transactions on

Publisher

ieee

ISSN

0018-9499

Type

jour

DOI

10.1109/23.173225

Filename

173225