Newton-style optimization for emission tomographic estimation

Jean-Baptiste Thibault; Ken D. Sauer; Charles A. Bouman

doi:10.1117/1.482754

1 July 2000 Newton-style optimization for emission tomographic estimation

Jean-Baptiste Thibault, Ken D. Sauer, Charles A. Bouman

Journal of Electronic Imaging, Vol. 9, Issue 3, (July 2000). https://doi.org/10.1117/1.482754

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.

Citation Download Citation

Jean-Baptiste Thibault, Ken D. Sauer, and Charles A. Bouman "Newton-style optimization for emission tomographic estimation," Journal of Electronic Imaging 9(3), (1 July 2000). https://doi.org/10.1117/1.482754

Published: 1 July 2000

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available