Tomographic image sequence reconstruction by edge-preserving interslice MAP methods

Author

Ding, Wei ; Liu, Bede

Author_Institution

Dept. of Electr. Eng., Princeton Univ., NJ, USA

Volume

5

Issue

1

fYear

1996

fDate

1/1/1996 12:00:00 AM

Firstpage

178

Lastpage

183

Abstract

We consider a new problem in tomographic imaging. In a sequence of transverse images, adjacent slices often look similar to each other. We investigate the possibility of using this correlation to help reconstruct the sequence with 2-D in-plane data. The problem is formulated as a maximum a posteriori (MAP) estimation problem, using an edge-preserving Markov random field prior model. Both Gaussian and Poisson data are considered. Some improvements over the single-slice MAP reconstructions are observed

Keywords

Markov processes; computerised tomography; emission tomography; image reconstruction; image sequences; maximum likelihood estimation; medical image processing; nondestructive testing; random processes; 2D in-plane data; Gaussian data; Poisson data; brain images; correlation; edge-preserving Markov random field prior model; edge-preserving interslice MAP methods; medical diagnostics; nondestructive materials testing; single-slice MAP reconstructions; tomographic image sequence reconstruction; transverse images; Detectors; Event detection; Image reconstruction; Image sequences; Iterative algorithms; Markov random fields; Materials testing; Medical diagnosis; Tomography; X-ray imaging;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.481687

Filename

481687