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Content Provider | IEEE Xplore Digital Library |
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Author | Razifar, P. Axelsson, J. Schneider, H. Langstrom, B. Bengtsson, E. Bergstrom, M. |
Copyright Year | 1963 |
Abstract | Most of the methods used for analyzing PET data are applied in the spatial domain (image domain), in which reconstructed images contain all different types of effects and errors caused by the reconstruction algorithm such as correlation in-between pixels, correlations in-between frames, and streak-artifacts. In this paper, we have investigated a new, pixel wise, noise prenormalization method used for transformation of input data followed by volume-wise application of principal component analysis (PCA) on masked dynamic PET data in the sinogram domain. We are aiming to improve the performance of PCA and to provide images with improved quality and signal extraction. We compare the performance of PCA and the image quality obtained with the new method with previously published approaches. The results show improvement of performance of PCA with respect to image quality, signal extraction, precision, and visualization |
Sponsorship | IEEE Nuclear and Plasma Sciences Society Computer Applications in Nuclear and Plasma Sciences (CANPS) Lawrence Berkeley Lab. Lawrence Livermore Nat. Lab. APS College of William and Mary Continuous Electron Beam Accelerator Facility NASA Defence Nuclear Agency Sandia National Laboratories Jet Propulsion Laboratory Brookhaven Nat. Lab. Lawrence Livermore Nat. Lab IEEE/NPPS Radiat. Effects Committee Defence Nuclear Agency/DoD Sandia National Laboratories/DOE Jet Propulsion Laboratory/NASA Phillips Lab./DoD |
Starting Page | 2759 |
Ending Page | 2768 |
Page Count | 10 |
File Size | 1457446 |
File Format | |
ISSN | 00189499 |
Volume Number | 53 |
Issue Number | 5 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2006-10-01 |
Publisher Place | U.S.A. |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Principal component analysis Positron emission tomography Image quality Cause effect analysis Data analysis Image analysis Algorithm design and analysis Image reconstruction Reconstruction algorithms Pixel volume-wise Masked dynamic data pixel wise noise prenormalization positron emission tomography (PET) principal component analysis (PCA) sinogram domain |
Content Type | Text |
Resource Type | Article |
Subject | Nuclear Energy and Engineering Electrical and Electronic Engineering Nuclear and High Energy Physics |
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