An SVD study of truncated transmission data in SPECT

Author

Zeng, Gengsheng L. ; Gullberg, Grant T.

Author_Institution

Dept. of Radiol., Utah Univ., Salt Lake City, UT, USA

Volume

44

Issue

1

fYear

1997

fDate

2/1/1997 12:00:00 AM

Firstpage

107

Lastpage

111

Abstract

Even though a noiseless, band-limited function is uniquely determined by its values in a local region, single photon emission computed tomography (SPECT) projections are not band-limited, and unmeasured projections may not be possible to be exactly estimated from the measured data. Projections from all views should be considered simultaneously and are modeled as a set of linear equations. The singular value decomposition (SVD) method is used to analyze and solve the equations. It is shown that truncation does not always result in an underdetermined problem, yet the problem may be ill-conditioned. An inaccurate pixel model may cause reconstruction artifacts via mismatch between the measured data and the modeled projections

Keywords

image reconstruction; medical image processing; single photon emission computed tomography; singular value decomposition; SPECT; SPECT projections; SVD study; ill-conditioned problem; inaccurate pixel model; linear equations; local region; mismatch; noiseless band-limited function; projections; reconstruction artifacts; single photon emission computed tomography; singular value decomposition; truncated transmission data; underdetermined problem; Attenuation; Cameras; Collimators; Equations; Image edge detection; Image reconstruction; Noise measurement; Optical computing; Single photon emission computed tomography; Singular value decomposition;

fLanguage

English

Journal_Title

Nuclear Science, IEEE Transactions on

Publisher

ieee

ISSN

0018-9499

Type

jour

DOI

10.1109/23.554833

Filename

554833