By Topic

Imaging glucose metabolism of brain using PET with clustering analysis for kinetics

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

7 Author(s)
Noshi, Y. ; Graduate Sch.of Sci. & Eng., Waseda Univ., Tokyo, Japan ; Yuichi Kimura ; Kenji Ishii ; Uchiyama, A.
more authors

The aim of this study is to visualize glucose metabolism in the brain using PET dynamic data and the proposed clustering analysis (CAKS). PET can give the glucose metabolism using 18F-FDG. Voxel-based analysis is not practical because of the bad noise property in voxel-based PET data and a large number of voxels. In CAKS, PET data are clustered to improve reliability in estimation and calculation speed. In CAKS, voxels whose concentration history in tissue time activity are similar, are gathered before parameter estimation using a statistical clustering algorithm based on the mixture Gaussian model, then the averaged time course is used for parameter estimation. As a result, physiologically acceptable images on the glucose metabolism were obtained in ten minutes.

Published in:

Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint  (Volume:2 )

Date of Conference:

2002