Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/69931
Title: Variational segmentation and PCA applied to dynamic PET analysis
Authors: Parker, B
Feng, DD
Keywords: Positron emission tomography
Variational segmentation
Principal component analysis
Graph theory
Issue Date: 2003
Publisher: Australian Computer Society
Source: Conferences in research and practice in information technology, May 2003, v. 22, p. 81-89 How to cite?
Journal: Conferences in research and practice in information technology 
Abstract: A graph-theoretic variational segmentation algorithm is applied to 22-frame dynamic positron emission tomography (PET) data sets after dimension reduction along the time axis using principal component analysis. Initial results indicate that the PCA is a very useful initial preprocessing step for segmentation and is effective in minimising the artifacts present in the PET data sets, allowing accurate delineation of pathological and anatomical features by the variational segmentation algorithm.
Description: 2002 Pan-Sydney Workshop on Visualisation (VIP'2002), Sydney, Australia, 2002
URI: http://hdl.handle.net/10397/69931
ISBN: 1-920682-01-5
ISSN: 1445-1336
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Google ScholarTM

Check



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.