Please use this identifier to cite or link to this item:
Title: Compression of dynamic PET based on principal component analysis and JPEG2000 in sinogram domain
Authors: Chen, Z
Feng, DD
Issue Date: 2003
Source: Proceedings, 7th International Conference on Digital Image Computing: Techniques and Application (DICTA'2003), Sydney, Australia, December 2003, p. 811-820 How to cite?
Abstract: A new algorithm for the compression of dynamic positron emission tomography (PET) data is presented. It consists of a temporal compression stage based on the application of principal component analysis (PCA) directly to the PET sinograms to reduce the dimensionality of the data. This is followed by a spatial compression stage using JPEG 2000 to each PCA channel weighted by the signal in each channel. By combining these temporal and spatial compression techniques we can achieve a compression ratio as high as 129:1 while simultaneously reducing noise and improving functional estimation compared with the uncompressed data, and preserving the sinogram data for later analysis. We validate our approach with a simulated phantom FDG brain study and clinical dynamic PET datasets. The results of performance evaluation suggest the new compression technique not only is able to reduce the original sinogram datasets by more than 95%, but also improve the reconstructed image quality for the quantitative analysis.
Appears in Collections:Conference Paper

Show full item record

Page view(s)

Last Week
Last month
Citations as of Jul 10, 2018

Google ScholarTM


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