SPECIAL SECTION ON MATHEMATICAL MODELING, STATISTICAL ESTIMATION, AND INVERSE PROBLEMS

Newton-style optimization for emission tomographic estimation

[+] Author Affiliations
Jean-Baptiste Thibault

General Electric Medical Systems, Global Technology Operations, W646, Waukesha, Wisconsin?53188

Ken Sauer

University of Notre Dame, Department of Electrical Engineering, Notre Dame, Indiana?46556

Charles A. Bouman

Purdue University, School of Electrical Engineering, West Lafayette, Indiana?47907-0501

J. Electron. Imaging. 9(3), 269-282 (Jul 01, 2000). doi:10.1117/1.482754
History: Received Sep. 30, 1999; Revised Nov. 15, 1999; Accepted Dec. 15, 1999
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Abstract

Emission computed tomography is widely applied in medical diagnostic imaging, especially to determine physiological function. The available set of measurements is, however, often incomplete and corrupted, and the quality of image reconstruction is enhanced by the computation of a statistically optimal estimate. Most formulations of the estimation problem use the Poisson model to measure fidelity to data. The intuitive appeal and operational simplicity of quadratic approximations to the Poisson log likelihood make them an attractive alternative, but they imply a potential loss of reconstruction quality which has not often been studied. This paper presents quantitative comparisons between the two models and shows that a judiciously chosen quadratic, as part of a short series of Newton-style steps, yields reconstructions nearly indistinguishable from those under the exact Poisson model. © 2000 SPIE and IS&T.

© 2000 SPIE and IS&T

Citation

Jean-Baptiste Thibault ; Ken Sauer and Charles A. Bouman
"Newton-style optimization for emission tomographic estimation", J. Electron. Imaging. 9(3), 269-282 (Jul 01, 2000). ; http://dx.doi.org/10.1117/1.482754


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