By Topic

Object-dependent performance comparison of two iterative reconstruction algorithms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Stamos, J.A. ; Dept. of Nucl. Eng., Michigan Univ., Ann Arbor, MI, USA ; Rogers, W.L. ; Clinthorne, N.H. ; Koral, K.F.

Iterative algorithms are of interest for both positron-emission tomography (PET) and single-photon-emission computed tomography (SPECT) because they permit accurate modeling of the imaging system, and they can be derived to satisfy certain statistical performance criteria. The convergence process, however, is influenced by the object distribution and noise level, so that different algorithms demonstrate a wide range of convergence phenomena. This object dependence is described for two widely accepted image-reconstruction algorithms; ART and maximum-likelihood estimation.

Published in:

Nuclear Science, IEEE Transactions on  (Volume:35 ,  Issue: 1 )