NDLI: Comparison of the convergence properties of the It-W and OS-EM algorithms in SPECT

Content Provider	IEEE Xplore Digital Library
Author	Wallis, J.W. Miller, T.R. Dai, G.M.
Copyright Year	1998
Description	Author affiliation: Mallinckrodt Inst. of Radiol., Washington Univ. Sch. of Med., St. Louis, MO, USA (Wallis, J.W.)
Abstract	Rapid convergence of iterative algorithms is a prerequisite for their clinical use in single-photon emission computed-tomography (SPECT). The rate of convergence of two accelerated methods, It-W (JNM, vol. 34, p. 1793, 1993) and ordered-subset expectation-maximization (OS-EM, IEEE-TMI, vol. 13, p. 601, 1994) were compared using a resolution phantom containing objects of sizes ranging from 1.0 to 2.5 cm. Object contrast was used as a measure of convergence. Attenuation and depth-dependent blur were modeled in the 90-angle projections and during reconstruction. For both methods, convergence was most rapid at the periphery and slowest in the center, with larger (lower frequency) objects converging most rapidly. When assessed under noise-free conditions, It-W converged 8-fold faster than 6-subset OS-EM, and 4-fold faster than 15-subset OS-EM. In an ensemble of 25 noisy images both methods gave essentially identical reconstructions when compared at equivalent noise levels using kernel-sieve regularization, but It-W converged 5 times faster than 15-subset OS-EM. Thus, the It-W method has a significant speed advantage for clinical application of iterative algorithms in SPECT, while retaining the favorable noise properties of the slower OS-FM and ML-EM reconstructions.
Starting Page	1752
Ending Page	1756
File Size	675328
Page Count	5
File Format	PDF
ISBN	0780342585
ISSN	10823654
DOI	10.1109/NSSMIC.1997.670655
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-11-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Convergence Iterative algorithms Imaging phantoms Acceleration Image reconstruction Image converters Reconstruction algorithms Biomedical imaging Attenuation Noise level
Content Type	Text
Resource Type	Article

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