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Non-isotropic noise correlation in PET data reconstructed by FBP but not by OSEM demonstrated using auto-correlation function
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics.
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry.
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2005 (English)In: Bio Medical Central (BMC): Medical Imaging, Vol. 5, no 3Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Positron emission tomography (PET) is a powerful imaging technique with the potential of obtaining functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules in a biological system, both in vitro and in vivo. PET images can be used directly or after kinetic modelling to extract quantitative values of a desired physiological, biochemical or pharmacological entity. Because such images are generally noisy, it is essential to understand how noise affects the derived quantitative values. A pre-requisite for this understanding is that the properties of noise such as variance (magnitude) and texture (correlation) are known. METHODS: In this paper we explored the pattern of noise correlation in experimentally generated PET images, with emphasis on the angular dependence of correlation, using the autocorrelation function (ACF). Experimental PET data were acquired in 2D and 3D acquisition mode and reconstructed by analytical filtered back projection (FBP) and iterative ordered subsets expectation maximisation (OSEM) methods. The 3D data was rebinned to a 2D dataset using FOurier REbinning (FORE) followed by 2D reconstruction using either FBP or OSEM. In synthetic images we compared the ACF results with those from covariance matrix. The results were illustrated as 1D profiles and also visualized as 2D ACF images. RESULTS: We found that the autocorrelation images from PET data obtained after FBP were not fully rotationally symmetric or isotropic if the object deviated from a uniform cylindrical radioactivity distribution. In contrast, similar autocorrelation images obtained after OSEM reconstruction were isotropic even when the phantom was not circular. Simulations indicated that the noise autocorrelation is non-isotropic in images created by FBP when the level of noise in projections is angularly variable. Comparison between 1D cross profiles on autocorrelation images obtained by FBP reconstruction and covariance matrices produced almost identical results in a simulation study. CONCLUSION: With asymmetric radioactivity distribution in PET, reconstruction using FBP, in contrast to OSEM, generates images in which the noise correlation is non-isotropic when the noise magnitude is angular dependent, such as in objects with asymmetric radioactivity distribution. In this respect, iterative reconstruction is superior since it creates isotropic noise correlations in the images.

Place, publisher, year, edition, pages
2005. Vol. 5, no 3
National Category
Computer Vision and Robotics (Autonomous Systems)
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URN: urn:nbn:se:uu:diva-74268DOI: 10.1186/1471-2342-5-3OAI: oai:DiVA.org:uu-74268DiVA: diva2:102178
Available from: 2005-09-19 Created: 2005-09-19 Last updated: 2017-02-13

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Razifar, PashaLångström, BengtBengtsson, Ewert

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Centre for Image AnalysisComputerized Image AnalysisDepartment of PhysicsDepartment of ChemistryDepartment of Neuroscience
Computer Vision and Robotics (Autonomous Systems)

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