Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26936
Title: Temporal processing of dynamic positron emission tomography via principal component analysis in the sinogram domain
Authors: Chen, Z
Parker, BJ
Feng, DD
Fulton, R
Keywords: Biomedical nuclear imaging
Image coding
Karhunen-Loeve transforms
Optimal sampling schedule
Positron emmision tomography
Principal component analysis
Issue Date: 2004
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on nuclear science, 2004, v. 51, no. 5 ii, p. 2612-2619 How to cite?
Journal: IEEE transactions on nuclear science 
Abstract: In this paper, we compare various temporal analysis schemes applied to dynamic PET for improved quantification, image quality and temporal compression purposes. We compare an optimal sampling schedule (OSS) design, principal component analysis (PCA) applied in the image domain, and principal component analysis applied in the sinogram domain; for region-of-interest quantification, sinogram-domain PCA is combined with the Huesman algorithm to quantify from the sinograms directly without requiring reconstruction of all PCA channels. Using a simulated phantom FDG brain study and three clinical studies, we evaluate the fidelity of the compressed data for estimation of local cerebral metabolic rate of glucose by a four-compartment model. Our results show that using a noise-normalized PCA in the sinogram domain gives similar compression ratio and quantitative accuracy to OSS, but with substantially better precision. These results indicate that sinogram-domain PCA for dynamic PET can be a useful preprocessing stage for PET compression and quantification applications.
URI: http://hdl.handle.net/10397/26936
ISSN: 0018-9499
EISSN: 1558-1578
DOI: 10.1109/TNS.2004.834816
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