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Activity Number: 221 - Contributed Poster Presentations: Section on Statistics in Imaging
Type: Contributed
Date/Time: Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
Sponsor: Section on Statistics in Imaging
Abstract #313303
Title: Quantification of Pixel-Wise Noise in Clinical Positron Emission Tomography (PET) Images
Author(s): Ran Ren* and Jian Huang and Finbarr O'Sullivan and Tian Mou and Kevin O'Regan
Companies: University College Cork and University College Cork and University College Cork and Karolinska Institutet and Cork University Hospital
Keywords: PET/CT; Re-binning; Attenuation; Gamma

Clinical PET/CT-FDG scanning is an important diagnostic tool applied in a number of prevalent cancers. Recently, our group have developed a Gamma model for modelling noise in iteratively reconstructed PET images and validated it on uniform phantom data (Tian et al 2017). In this study we develop a novel method for estimation of local Gamma model parameters associated with non-uniform sources. The estimation method is based on combination of local homogeneity and attenuation effects and consists of two steps: 1. For each pixel, we estimate local Gamma parameters by fitting gamma distribution to a local VOI centered at that pixel; 2. We refine estimates based on the attenuation map (Kueng et al 2017). The techniques is evaluated using 31 lung cancer patients data from clinical whole-body scanning with reconstructed consecutive 1-minute time-frames. The analysis finds that there is strong agreement between the directly estimated using consecutive 1-minute time-frames and constructed by the proposed approach involving only the single 1-minute frame information.

Authors who are presenting talks have a * after their name.

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