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- W4295035963 abstract "We have developed a prototype 1-mm resolution dual panel positron emission tomography (PET) system for clinical cancer imaging. When completed, each panel of the system will contain 98,304 lutetium-yttrium oxyorthosilicate (LYSO) crystal elements, and the system will incorporate approximately 9.7 billion distinct crystal pairs, each of which allows the formation of a line-of-response (LOR). Performing a direct normalization on the system is extremely difficult since it is practically impossible to acquire a statistically significant number of coincidence events to estimate all the crystal-pair sensitivities. To overcome this challenge, we propose a component-based normalization method specific to this system but also useful in other PET systems comprising billions of LORs. Firstly, we decompose a singles-mode crystal sensitivity into crystal efficiency and geometric components, and analytically calculate the geometric components using a graphics processing unit (GPU) acceleration. Crystal efficiencies are then estimated from singles-mode datasets. Secondly, geometric components in coincidence mode scans are analytically estimated. Lastly, crystal-pair sensitivities, which will be used as normalization coefficients, are calculated by combining the crystal efficiencies calculated in Step 1, and the geometric component of each crystal pair calculated in Step 2. In this work, the first two steps were performed and validated. Singles-mode geometric components predict counts per crystal measured in GATE simulations with R <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> above 85%, and a back-projected image of a coincidence-mode geometric components predict an image reconstructed from a GATE simulation with R <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> of 98%." @default.
- W4295035963 created "2022-09-09" @default.
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- W4295035963 date "2021-10-16" @default.
- W4295035963 modified "2023-10-16" @default.
- W4295035963 title "Component-Based Normalization for a 1-Millimeter Resolution Clinical PET System Comprising 10 Billion LORs Using Analytical Estimations with GPU Acceleration" @default.
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- W4295035963 doi "https://doi.org/10.1109/nss/mic44867.2021.9875730" @default.
- W4295035963 hasPublicationYear "2021" @default.
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