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