Share Email Print

Proceedings Paper

Cerebral Blood Flow Estimation Using Classification Techniques On A Sequence Of Low Resolution Tomographic Evolutive Images
Author(s): Marie Chan; Joseph Aguilar-Martin; Kader Boulanouar; Pierre Celsis; Jean Pierre Marc-Vergnes
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In order to improve the performance of the instrumental variable method (IVM) in calculating regional cerebral blood flow (rCBF) using Single Photon Emission Computed Tomography (SPELT), and inert diffusible tracer such as 133Xe, we use Learning Algorithms for Multivariate Data Analysis (LAMDA) to classify the voxels of the images of local concentrations in the brain. The LAMDA method correctly distinguished between extra and intra-cerebral voxels. However the topography of the intra-cerebral classes did not match the Regions Of Interest (ROI) defined on an anatomical basis. Provided that all the intra-cerebral classes contaminated by bone and air passage artefact were rejected, the results given by the NM are in good agreement with those derived by the bolus distribution principle. We thus conclude that LAMDA methods can improve the reliability of images of CBF estimates.

Paper Details

Date Published: 1 May 1989
PDF: 11 pages
Proc. SPIE 1090, Medical Imaging III: Image Formation, (1 May 1989); doi: 10.1117/12.953197
Show Author Affiliations
Marie Chan, Unite 230 Inserm (France)
Joseph Aguilar-Martin, LAAS du CNRS (France)
Kader Boulanouar, Unite 230 Inserm (France)
Pierre Celsis, Unite 230 Inserm (France)
Jean Pierre Marc-Vergnes, Unite 230 Inserm (France)

Published in SPIE Proceedings Vol. 1090:
Medical Imaging III: Image Formation
Samuel J. Dwyer; R. Gilbert Jost; Roger H. Schneider, Editor(s)

© SPIE. Terms of Use
Back to Top