By Topic

Statistical image reconstruction methods in PET with compensation for missing data

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
$33 $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

3 Author(s)
P. E. Kinahan ; Dept. of Radiol., Pittsburgh Univ., PA, USA ; J. A. Fessler ; J. S. Karp

We present the results of combining volume imaging with the PENN-PET scanner with statistical image reconstruction methods such as the penalized weighted least squares (PWLS) method. The goal of this particular combination is to improve both classification and estimation tasks in PET imaging protocols where image quality is dominated by spatially-variant system responses and/or measurement statistics. The PENN-PET scanner has strongly spatially-varying system behavior due to its volume imaging design and the presence of detector gaps. Statistical methods are easily adapted to this scanner geometry, including the detector gaps, and have also been shown to have improved bias/variance trade-offs compared to the standard filtered-backprojection (FBP) reconstruction method. The PWLS method requires fewer iterations and may be more tolerant of errors in the system model than other statistical methods. We present results demonstrating the improvement in image quality for PWLS image reconstructions of data from the PENN-PET scanner

Published in:

Nuclear Science Symposium, 1996. Conference Record., 1996 IEEE  (Volume:3 )

Date of Conference:

2-9 Nov 1996